| Title: | Conversion of R Regression Output to LaTeX or HTML Tables |
|---|---|
| Description: | Converts coefficients, standard errors, significance stars, and goodness-of-fit statistics of statistical models into LaTeX tables or HTML tables/MS Word documents or to nicely formatted screen output for the R console for easy model comparison. A list of several models can be combined in a single table. The output is highly customizable. New model types can be easily implemented. Details can be found in Leifeld (2013), JStatSoft <doi:10.18637/jss.v055.i08>.) |
| Authors: | Philip Leifeld [aut, cre], Claudia Zucca [ctb] |
| Maintainer: | Philip Leifeld <[email protected]> |
| License: | GPL-3 |
| Version: | 1.39.4 |
| Built: | 2024-11-20 04:51:53 UTC |
| Source: | https://github.com/leifeld/texreg |
texreg converts coefficients, standard errors, uncertainty measures, and goodness-of-fit statistics of statistical models into LaTeX or HTML tables or into nicely formatted screen output for the R console. A list of several models can be combined in a single table. The output is customizable. New model types can be easily implemented. Confidence intervals can be used instead of standard errors and p-values.
Philip Leifeld
Leifeld, Philip (2013). texreg: Conversion of Statistical Model Output in R to LaTeX and HTML Tables. Journal of Statistical Software 55(8): 1-24. doi:10.18637/jss.v055.i08.
Constructor for texreg objects.
createTexreg( coef.names, coef, se = numeric(0), pvalues = numeric(0), ci.low = numeric(0), ci.up = numeric(0), gof.names = character(0), gof = numeric(0), gof.decimal = logical(0), model.name = character(0) )createTexreg( coef.names, coef, se = numeric(0), pvalues = numeric(0), ci.low = numeric(0), ci.up = numeric(0), gof.names = character(0), gof = numeric(0), gof.decimal = logical(0), model.name = character(0) )
coef.names |
The names for the covariates in a model as a
|
coef |
The coefficients as a |
se |
The standard errors as a |
pvalues |
The p-values as a |
ci.low |
The lower bounds of the confidence intervals as a
|
ci.up |
The upper bounds of the confidence intervals as a
|
gof.names |
Names of the goodness-of-fit statistics as a
|
gof |
Goodness-of-fit statistics as a |
gof.decimal |
A |
model.name |
A name for the statistical model. Can be a |
This function creates a texreg object. A texreg
object contains information about coefficients, standard errors, p-values
(optional), and about goodness-of-fit statistics. Instead of standard
errors and p-values, a texreg object may also contain upper and
lower bounds of a confidence interval. texreg objects are used
by the texreg function to create LaTeX tables and other
representations of the model results.
A texreg object representing the statistical model.
Philip Leifeld
Leifeld, Philip (2013). texreg: Conversion of Statistical Model Output in R to LaTeX and HTML Tables. Journal of Statistical Software 55(8): 1-24. doi:10.18637/jss.v055.i08.
library("nlme") # load library for fitting linear mixed effects models model <- lme(distance ~ age, data = Orthodont, random = ~ 1) # estimate coefficient.names <- rownames(summary(model)$tTable) # extract coef names coefficients <- summary(model)$tTable[, 1] # extract coefficient values standard.errors <- summary(model)$tTable[, 2] # extract standard errors significance <- summary(model)$tTable[, 5] #extract p-values lik <- summary(model)$logLik # extract log likelihood aic <- summary(model)$AIC # extract AIC bic <- summary(model)$BIC # extract BIC n <- nobs(model) # extract number of observations gof <- c(aic, bic, lik, n) # create a vector of GOF statistics gof.names <- c("AIC", "BIC", "Log Likelihood", "Num. obs.") # names of GOFs decimal.places <- c(TRUE, TRUE, TRUE, FALSE) # last one is a count variable # create the texreg object tr <- createTexreg(coef.names = coefficient.names, coef = coefficients, se = standard.errors, pvalues = significance, gof.names = gof.names, gof = gof, gof.decimal = decimal.places)library("nlme") # load library for fitting linear mixed effects models model <- lme(distance ~ age, data = Orthodont, random = ~ 1) # estimate coefficient.names <- rownames(summary(model)$tTable) # extract coef names coefficients <- summary(model)$tTable[, 1] # extract coefficient values standard.errors <- summary(model)$tTable[, 2] # extract standard errors significance <- summary(model)$tTable[, 5] #extract p-values lik <- summary(model)$logLik # extract log likelihood aic <- summary(model)$AIC # extract AIC bic <- summary(model)$BIC # extract BIC n <- nobs(model) # extract number of observations gof <- c(aic, bic, lik, n) # create a vector of GOF statistics gof.names <- c("AIC", "BIC", "Log Likelihood", "Num. obs.") # names of GOFs decimal.places <- c(TRUE, TRUE, TRUE, FALSE) # last one is a count variable # create the texreg object tr <- createTexreg(coef.names = coefficient.names, coef = coefficients, se = standard.errors, pvalues = significance, gof.names = gof.names, gof = gof, gof.decimal = decimal.places)
Extract details from statistical models for table construction. The function has methods for a range of statistical models.
extract(model, ...)extract(model, ...)
model |
A statistical model object. |
... |
Custom parameters, which are handed over to subroutines. The
arguments are usually passed to the |
The extract function serves to retrieve coefficients, standard
errors, p-values, confidence intervals, and goodness-of-fit statistics from
statistical models in R. More than 100 extract methods
("extensions") for various statistical models are available. The function
returns a texreg object.
extract is a generic function, which extracts coefficients and
GOF measures from statistical model objects. extract methods
for the specific model types are called by the generic extract
function if it encounters a model known to be handled by the specific method.
The output is a texreg object, which is subsequently used by
the texreg function and related functions.
To list the model classes for which extract methods exist, type
showMethods("extract") or methods("extract"). To show the
method definition (i.e., the function body) of a specific extract method, use
the getMethod function, for example getMethod("extract", "lm")
for linear models. To get help on a specific extract method, type something
like ?`extract,lm-method` (or something similar for other models,
where "lm" needs to be replaced by the class name of the respective
model). You can also list the available methods by displaying the
texreg package help index.
Users can contribute their own extensions for additional statistical models. Examples are contained in the article in the Journal of Statistical Software referenced below. Suggestions can be submitted as pull requests at https://github.com/leifeld/texreg/pulls or through the issue tracker at https://github.com/leifeld/texreg/issues.
The function returns a texreg object.
Philip Leifeld
Leifeld, Philip (2013). texreg: Conversion of Statistical Model Output in R to LaTeX and HTML Tables. Journal of Statistical Software 55(8): 1-24. doi:10.18637/jss.v055.i08.
createTexreg, matrixreg,
screenreg, texreg
extract method for aftreg objectsextract method for aftreg objects created by the
aftreg function in the eha package.
## S4 method for signature 'aftreg' extract( model, include.aic = TRUE, include.loglik = TRUE, include.lr = TRUE, include.nobs = TRUE, include.events = TRUE, include.trisk = TRUE, ... )## S4 method for signature 'aftreg' extract( model, include.aic = TRUE, include.loglik = TRUE, include.lr = TRUE, include.nobs = TRUE, include.events = TRUE, include.trisk = TRUE, ... )
model |
A statistical model object. |
include.aic |
Report Akaike's Information Criterion (AIC) in the GOF block? |
include.loglik |
Report the log likelihood in the GOF block? |
include.lr |
Report likelihood ratio test? |
include.nobs |
Report the number of observations in the GOF block? |
include.events |
Report the number of events in the GOF block? |
include.trisk |
Report the total time at risk (in event-history models)? |
... |
Custom parameters, which are handed over to subroutines. Currently not in use. |
extract method for broom objectsextract method for broom objects created by the
broom function in the broom package.
## S4 method for signature 'ANY' extract(model, ...)## S4 method for signature 'ANY' extract(model, ...)
model |
A statistical model object. |
... |
Custom parameters, which are handed over to subroutines. Currently not in use. |
extract method for Arima objectsextract method for Arima objects created by the
arima function in the stats package.
## S4 method for signature 'Arima' extract( model, include.pvalues = TRUE, include.aic = TRUE, include.bic = TRUE, include.loglik = TRUE, include.nobs = TRUE, ... )## S4 method for signature 'Arima' extract( model, include.pvalues = TRUE, include.aic = TRUE, include.bic = TRUE, include.loglik = TRUE, include.nobs = TRUE, ... )
model |
A statistical model object. |
include.pvalues |
Report p-values? |
include.aic |
Report Akaike's Information Criterion (AIC) in the GOF block? |
include.bic |
Report the Bayesian Information Criterion (BIC) in the GOF block? |
include.loglik |
Report the log likelihood in the GOF block? |
include.nobs |
Report the number of observations in the GOF block? |
... |
Custom parameters, which are handed over to subroutines. Currently not in use. |
extract method for averaging objectsextract method for averaging objects created by the
model.avg function in the MuMIn package.
## S4 method for signature 'averaging' extract(model, use.ci = FALSE, adjusted.se = FALSE, include.nobs = TRUE, ...)## S4 method for signature 'averaging' extract(model, use.ci = FALSE, adjusted.se = FALSE, include.nobs = TRUE, ...)
model |
A statistical model object. |
use.ci |
Report confidence intervals in the GOF block? |
adjusted.se |
Report adjusted standard error in the GOF block? |
include.nobs |
Report the number of observations in the GOF block? |
... |
Custom parameters, which are handed over to subroutines. Currently not in use. |
extract method for bam objectsextract method for bam objects created by the
bam function in the mgcv package.
## S4 method for signature 'bam' extract( model, include.smooth = TRUE, include.aic = TRUE, include.bic = TRUE, include.loglik = TRUE, include.deviance = TRUE, include.dev.expl = TRUE, include.dispersion = TRUE, include.rsquared = TRUE, include.gcv = TRUE, include.nobs = TRUE, include.nsmooth = TRUE, ... )## S4 method for signature 'bam' extract( model, include.smooth = TRUE, include.aic = TRUE, include.bic = TRUE, include.loglik = TRUE, include.deviance = TRUE, include.dev.expl = TRUE, include.dispersion = TRUE, include.rsquared = TRUE, include.gcv = TRUE, include.nobs = TRUE, include.nsmooth = TRUE, ... )
model |
A statistical model object. |
include.smooth |
Report the smooth terms of a GAM? If they are reported, the EDF value is reported as the coefficient, and DF is included in parentheses (not standard errors because a chi-square test is used for the smooth terms). |
include.aic |
Report Akaike's Information Criterion (AIC) in the GOF block? |
include.bic |
Report the Bayesian Information Criterion (BIC) in the GOF block? |
include.loglik |
Report the log likelihood in the GOF block? |
include.deviance |
Report the deviance? |
include.dev.expl |
Report the deviance explained? |
include.dispersion |
Report the dispersion parameter? |
include.rsquared |
Report R^2 in the GOF block? |
include.gcv |
Report the GCV score? |
include.nobs |
Report the number of observations in the GOF block? |
include.nsmooth |
Report the number of smooth terms? |
... |
Custom parameters, which are handed over to subroutines, in this
case to the |
extract method for bergm objectsextract method for bergm objects created by the
bergm function in the Bergm package.
## S4 method for signature 'bergm' extract(model, posterior.median = FALSE, level = 0.95, ...)## S4 method for signature 'bergm' extract(model, posterior.median = FALSE, level = 0.95, ...)
model |
A statistical model object. |
posterior.median |
Report the posterior median instead of the default posterior mean as coefficients? |
level |
Confidence level, i.e., the proportion of the posterior distribution to be included in the credible interval. |
... |
Custom parameters, which are handed over to subroutines. Currently not in use. |
extract method for betamfx objectsextract method for betamfx objects created by the
betamfx function in the mfx package.
## S4 method for signature 'betamfx' extract( model, include.pseudors = TRUE, include.loglik = TRUE, include.nobs = TRUE, ... )## S4 method for signature 'betamfx' extract( model, include.pseudors = TRUE, include.loglik = TRUE, include.nobs = TRUE, ... )
model |
A statistical model object. |
include.pseudors |
Report pseudo R^2 in the GOF block? |
include.loglik |
Report the log likelihood in the GOF block? |
include.nobs |
Report the number of observations in the GOF block? |
... |
Custom parameters, which are handed over to subroutines. Currently not in use. |
extract method for betaor objectsextract method for betaor objects created by the
betaor function in the mfx package.
## S4 method for signature 'betaor' extract( model, include.pseudors = TRUE, include.loglik = TRUE, include.nobs = TRUE, ... )## S4 method for signature 'betaor' extract( model, include.pseudors = TRUE, include.loglik = TRUE, include.nobs = TRUE, ... )
model |
A statistical model object. |
include.pseudors |
Report pseudo R^2 in the GOF block? |
include.loglik |
Report the log likelihood in the GOF block? |
include.nobs |
Report the number of observations in the GOF block? |
... |
Custom parameters, which are handed over to subroutines. Currently not in use. |
extract method for betareg objectsextract method for betareg objects created by the
betareg function in the betareg package.
## S4 method for signature 'betareg' extract( model, include.precision = TRUE, include.pseudors = TRUE, include.loglik = TRUE, include.nobs = TRUE, ... )## S4 method for signature 'betareg' extract( model, include.precision = TRUE, include.pseudors = TRUE, include.loglik = TRUE, include.nobs = TRUE, ... )
model |
A statistical model object. |
include.precision |
Report precision in the GOF block? |
include.pseudors |
Report pseudo R^2 in the GOF block? |
include.loglik |
Report the log likelihood in the GOF block? |
include.nobs |
Report the number of observations in the GOF block? |
... |
Custom parameters, which are handed over to subroutines, in this
case to the |
extract method for bife objectsextract method for bife objects created by the
bife function in the bife package.
## S4 method for signature 'bife' extract( model, include.loglik = TRUE, include.deviance = TRUE, include.nobs = TRUE, ... )## S4 method for signature 'bife' extract( model, include.loglik = TRUE, include.deviance = TRUE, include.nobs = TRUE, ... )
model |
A statistical model object. |
include.loglik |
Report the log likelihood in the GOF block? |
include.deviance |
Report the residual deviance? |
include.nobs |
Report the number of observations in the GOF block? |
... |
Custom parameters, which are handed over to subroutines. Currently not in use. |
Philip Leifeld, Christoph Riedl, Claudia Zucca
extract method for biglm objectsextract method for biglm objects created by the
biglm function in the biglm package.
## S4 method for signature 'biglm' extract(model, include.nobs = TRUE, include.aic = TRUE, use.ci = FALSE, ...)## S4 method for signature 'biglm' extract(model, include.nobs = TRUE, include.aic = TRUE, use.ci = FALSE, ...)
model |
A statistical model object. |
include.nobs |
Report the number of observations in the GOF block? |
include.aic |
Report Akaike's Information Criterion (AIC) in the GOF block? |
use.ci |
Report confidence intervals in the GOF block? |
... |
Custom parameters, which are handed over to subroutines. Currently not in use. |
Claudia Zucca, Philip Leifeld
extract method for brglm objectsextract method for brglm objects created by the
brglm function in the brglm package.
## S4 method for signature 'brglm' extract( model, include.aic = TRUE, include.bic = TRUE, include.loglik = TRUE, include.deviance = TRUE, include.nobs = TRUE, ... )## S4 method for signature 'brglm' extract( model, include.aic = TRUE, include.bic = TRUE, include.loglik = TRUE, include.deviance = TRUE, include.nobs = TRUE, ... )
model |
A statistical model object. |
include.aic |
Report Akaike's Information Criterion (AIC) in the GOF block? |
include.bic |
Report the Bayesian Information Criterion (BIC) in the GOF block? |
include.loglik |
Report the log likelihood in the GOF block? |
include.deviance |
Report the deviance? |
include.nobs |
Report the number of observations in the GOF block? |
... |
Custom parameters, which are handed over to subroutines, in this
case to the |
extract method for brmsfit objectsextract method for brmsfit objects created by the
brm function in the brms package.
## S4 method for signature 'brmsfit' extract( model, use.HDI = TRUE, level = 0.9, include.random = TRUE, include.rsquared = TRUE, include.nobs = TRUE, include.loo.ic = TRUE, reloo = FALSE, include.waic = TRUE, ... )## S4 method for signature 'brmsfit' extract( model, use.HDI = TRUE, level = 0.9, include.random = TRUE, include.rsquared = TRUE, include.nobs = TRUE, include.loo.ic = TRUE, reloo = FALSE, include.waic = TRUE, ... )
model |
A statistical model object. |
use.HDI |
Report highest posterior density (HPD) intervals (HDI) using
the |
level |
Significance level ( |
include.random |
Include random effects (standard deviations) in the GOF block of the table? |
include.rsquared |
Report R^2 in the GOF block? |
include.nobs |
Report the number of observations in the GOF block? |
include.loo.ic |
Report Leave-One-Out Information Criterion? |
reloo |
Recompute exact cross-validation for problematic observations
for which approximate leave-one-out cross-validation may return incorrect
results? This is done using the |
include.waic |
Report Widely Applicable Information Criterion (WAIC)? |
... |
Custom parameters, which are handed over to subroutines, in this
case to the |
Hyunjin (Jin) Song, Philip Leifeld
extract method for btergm objectsextract method for btergm objects created by the
btergm function in the btergm package.
## S4 method for signature 'btergm' extract(model, level = 0.95, include.nobs = TRUE, ...)## S4 method for signature 'btergm' extract(model, level = 0.95, include.nobs = TRUE, ...)
model |
A statistical model object. |
level |
Significance or confidence level ( |
include.nobs |
Report the number of observations in the GOF block? |
... |
Custom parameters, which are handed over to subroutines. Currently not in use. |
extract method for censReg objectsextract method for censReg objects created by the
censReg function in the censReg package.
## S4 method for signature 'censReg' extract( model, include.aic = TRUE, include.bic = TRUE, include.loglik = TRUE, include.nobs = TRUE, ... )## S4 method for signature 'censReg' extract( model, include.aic = TRUE, include.bic = TRUE, include.loglik = TRUE, include.nobs = TRUE, ... )
model |
A statistical model object. |
include.aic |
Report Akaike's Information Criterion (AIC) in the GOF block? |
include.bic |
Report the Bayesian Information Criterion (BIC) in the GOF block? |
include.loglik |
Report the log likelihood in the GOF block? |
include.nobs |
Report the number of observations in the GOF block? |
... |
Custom parameters, which are handed over to subroutines, in this
case to the |
extract method for clm objectsextract method for clm objects created by the
clm function in the ordinal package.
## S4 method for signature 'clm' extract( model, include.thresholds = TRUE, include.aic = TRUE, include.bic = TRUE, include.loglik = TRUE, include.nobs = TRUE, ... )## S4 method for signature 'clm' extract( model, include.thresholds = TRUE, include.aic = TRUE, include.bic = TRUE, include.loglik = TRUE, include.nobs = TRUE, ... )
model |
A statistical model object. |
include.thresholds |
Report thresholds in the GOF block? |
include.aic |
Report Akaike's Information Criterion (AIC) in the GOF block? |
include.bic |
Report the Bayesian Information Criterion (BIC) in the GOF block? |
include.loglik |
Report the log likelihood in the GOF block? |
include.nobs |
Report the number of observations in the GOF block? |
... |
Custom parameters, which are handed over to subroutines, in this
case to the |
extract method for clmm objectsextract method for clmm objects created by the
clmm function in the ordinal package.
## S4 method for signature 'clmm' extract( model, include.thresholds = TRUE, include.loglik = TRUE, include.aic = TRUE, include.bic = TRUE, include.nobs = TRUE, include.groups = TRUE, include.variance = TRUE, ... )## S4 method for signature 'clmm' extract( model, include.thresholds = TRUE, include.loglik = TRUE, include.aic = TRUE, include.bic = TRUE, include.nobs = TRUE, include.groups = TRUE, include.variance = TRUE, ... )
model |
A statistical model object. |
include.thresholds |
Report thresholds in the GOF block? |
include.loglik |
Report the log likelihood in the GOF block? |
include.aic |
Report Akaike's Information Criterion (AIC) in the GOF block? |
include.bic |
Report the Bayesian Information Criterion (BIC) in the GOF block? |
include.nobs |
Report the number of observations in the GOF block? |
include.groups |
Report the number of groups? |
include.variance |
Report group variances? |
... |
Custom parameters, which are handed over to subroutines, in this
case to the |
extract method for clogit objectsextract method for clogit objects created by the
clogit function in the survival package.
## S4 method for signature 'clogit' extract( model, include.aic = TRUE, include.rsquared = TRUE, include.maxrs = TRUE, include.events = TRUE, include.nobs = TRUE, include.missings = TRUE, ... )## S4 method for signature 'clogit' extract( model, include.aic = TRUE, include.rsquared = TRUE, include.maxrs = TRUE, include.events = TRUE, include.nobs = TRUE, include.missings = TRUE, ... )
model |
A statistical model object. |
include.aic |
Report Akaike's Information Criterion (AIC) in the GOF block? |
include.rsquared |
Report R^2 in the GOF block? |
include.maxrs |
Report maximal R^2 in the GOF block? |
include.events |
Report the number of events in the GOF block? |
include.nobs |
Report the number of observations in the GOF block? |
include.missings |
Report number of missing data points in the GOF block? |
... |
Custom parameters, which are handed over to subroutines, in this
case to the |
extract method for coeftest objectsextract method for coeftest objects created by the
coeftest function in the lmtest package.
## S4 method for signature 'coeftest' extract(model, ...)## S4 method for signature 'coeftest' extract(model, ...)
model |
A statistical model object. |
... |
Custom parameters, which are handed over to subroutines. Currently not in use. |
extract method for coxph objectsextract method for coxph objects created by the
coxph function in the survival package.
## S4 method for signature 'coxph' extract( model, include.aic = TRUE, include.rsquared = TRUE, include.maxrs = TRUE, include.events = TRUE, include.nobs = TRUE, include.missings = TRUE, include.zph = TRUE, ... )## S4 method for signature 'coxph' extract( model, include.aic = TRUE, include.rsquared = TRUE, include.maxrs = TRUE, include.events = TRUE, include.nobs = TRUE, include.missings = TRUE, include.zph = TRUE, ... )
model |
A statistical model object. |
include.aic |
Report Akaike's Information Criterion (AIC) in the GOF block? |
include.rsquared |
Report R^2 in the GOF block? |
include.maxrs |
Report maximal R^2 in the GOF block? |
include.events |
Report the number of events in the GOF block? |
include.nobs |
Report the number of observations in the GOF block? |
include.missings |
Report number of missing data points in the GOF block? |
include.zph |
Report proportional hazard test in the GOF block? |
... |
Custom parameters, which are handed over to subroutines, in this
case to the |
extract method for coxph.penal objectsextract method for coxph.penal objects created by the
coxph function in the survival package.
## S4 method for signature 'coxph.penal' extract( model, include.aic = TRUE, include.rsquared = TRUE, include.maxrs = TRUE, include.events = TRUE, include.nobs = TRUE, include.missings = TRUE, include.zph = TRUE, ... )## S4 method for signature 'coxph.penal' extract( model, include.aic = TRUE, include.rsquared = TRUE, include.maxrs = TRUE, include.events = TRUE, include.nobs = TRUE, include.missings = TRUE, include.zph = TRUE, ... )
model |
A statistical model object. |
include.aic |
Report Akaike's Information Criterion (AIC) in the GOF block? |
include.rsquared |
Report R^2 in the GOF block? |
include.maxrs |
Report maximal R^2 in the GOF block? |
include.events |
Report the number of events in the GOF block? |
include.nobs |
Report the number of observations in the GOF block? |
include.missings |
Report number of missing data points in the GOF block? |
include.zph |
Report proportional hazard test in the GOF block? |
... |
Custom parameters, which are handed over to subroutines, in this
case to the |
extract method for coxreg objectsextract method for coxreg objects created by the
coxreg function in the eha package.
## S4 method for signature 'coxreg' extract( model, include.aic = TRUE, include.loglik = TRUE, include.lr = TRUE, include.nobs = TRUE, include.events = TRUE, include.trisk = TRUE, ... )## S4 method for signature 'coxreg' extract( model, include.aic = TRUE, include.loglik = TRUE, include.lr = TRUE, include.nobs = TRUE, include.events = TRUE, include.trisk = TRUE, ... )
model |
A statistical model object. |
include.aic |
Report Akaike's Information Criterion (AIC) in the GOF block? |
include.loglik |
Report the log likelihood in the GOF block? |
include.lr |
Report likelihood ratio test? |
include.nobs |
Report the number of observations in the GOF block? |
include.events |
Report the number of events in the GOF block? |
include.trisk |
Report the total time at risk (in event-history models)? |
... |
Custom parameters, which are handed over to subroutines. Currently not in use. |
extract method for dynlm objectsextract method for dynlm objects created by the
dynlm function in the dynlm package.
## S4 method for signature 'dynlm' extract( model, include.rsquared = TRUE, include.adjrs = TRUE, include.nobs = TRUE, include.fstatistic = FALSE, include.rmse = FALSE, ... )## S4 method for signature 'dynlm' extract( model, include.rsquared = TRUE, include.adjrs = TRUE, include.nobs = TRUE, include.fstatistic = FALSE, include.rmse = FALSE, ... )
model |
A statistical model object. |
include.rsquared |
Report R^2 in the GOF block? |
include.adjrs |
Report adjusted R^2 in the GOF block? |
include.nobs |
Report the number of observations in the GOF block? |
include.fstatistic |
Report the F-statistic in the GOF block? |
include.rmse |
Report the root mean square error (RMSE; = residual standard deviation) in the GOF block? |
... |
Custom parameters, which are handed over to subroutines, in this
case to the |
extract method for ergm objectsextract method for ergm objects created by the
ergm function in the ergm package.
## S4 method for signature 'ergm' extract( model, include.aic = TRUE, include.bic = TRUE, include.loglik = TRUE, ... )## S4 method for signature 'ergm' extract( model, include.aic = TRUE, include.bic = TRUE, include.loglik = TRUE, ... )
model |
A statistical model object. |
include.aic |
Report Akaike's Information Criterion (AIC) in the GOF block? |
include.bic |
Report the Bayesian Information Criterion (BIC) in the GOF block? |
include.loglik |
Report the log likelihood in the GOF block? |
... |
Custom parameters, which are handed over to subroutines, in this
case to the |
extract method for ergmm objectsextract method for ergmm objects created by the
ergmm function in the latentnet
package.
## S4 method for signature 'ergmm' extract(model, include.bic = TRUE, ...)## S4 method for signature 'ergmm' extract(model, include.bic = TRUE, ...)
model |
A statistical model object. |
include.bic |
Report the Bayesian Information Criterion (BIC) in the GOF block? |
... |
Custom parameters, which are handed over to subroutines. Currently not in use. |
extract method for ets objectsextract method for ets objects created by the
ets function in the forecast package.
## S4 method for signature 'ets' extract( model, include.pvalues = FALSE, include.aic = TRUE, include.aicc = TRUE, include.bic = TRUE, include.loglik = TRUE, ... )## S4 method for signature 'ets' extract( model, include.pvalues = FALSE, include.aic = TRUE, include.aicc = TRUE, include.bic = TRUE, include.loglik = TRUE, ... )
model |
A statistical model object. |
include.pvalues |
Report p-values? |
include.aic |
Report Akaike's Information Criterion (AIC) in the GOF block? |
include.aicc |
Report AICC in the GOF block? |
include.bic |
Report the Bayesian Information Criterion (BIC) in the GOF block? |
include.loglik |
Report the log likelihood in the GOF block? |
... |
Custom parameters, which are handed over to subroutines. Currently not in use. |
extract method for feglm objectsextract method for feglm objects created by the
feglm function in the alpaca package.
## S4 method for signature 'feglm' extract( model, include.deviance = TRUE, include.nobs = TRUE, include.groups = TRUE, ... )## S4 method for signature 'feglm' extract( model, include.deviance = TRUE, include.nobs = TRUE, include.groups = TRUE, ... )
model |
A statistical model object. |
include.deviance |
Report the deviance? |
include.nobs |
Report the number of observations in the GOF block? |
include.groups |
Report the number of groups? |
... |
Custom parameters, which are handed over to subroutines, in this
case to the |
Christoph Riedl, Oliver Reiter, Philip Leifeld
extract method for feis objectsextract method for feis objects created by the
feis function in the feisr package.
## S4 method for signature 'feis' extract( model, include.rsquared = TRUE, include.adjrs = TRUE, include.nobs = TRUE, include.groups = TRUE, include.rmse = TRUE, ... )## S4 method for signature 'feis' extract( model, include.rsquared = TRUE, include.adjrs = TRUE, include.nobs = TRUE, include.groups = TRUE, include.rmse = TRUE, ... )
model |
A statistical model object. |
include.rsquared |
Report R^2 in the GOF block? |
include.adjrs |
Report adjusted R^2 in the GOF block? |
include.nobs |
Report the number of observations in the GOF block? |
include.groups |
Report the number of groups? |
include.rmse |
Report the root mean square error (RMSE; = residual standard deviation) in the GOF block? |
... |
Custom parameters, which are handed over to subroutines, in this
case to the |
Tobias Rüttenauer, Philip Leifeld
extract method for felm objectsextract method for felm objects created by the
felm function in the lfe package.
## S4 method for signature 'felm' extract( model, include.nobs = TRUE, include.rsquared = TRUE, include.adjrs = TRUE, include.fstatistic = FALSE, include.proj.stats = TRUE, include.groups = TRUE, ... )## S4 method for signature 'felm' extract( model, include.nobs = TRUE, include.rsquared = TRUE, include.adjrs = TRUE, include.fstatistic = FALSE, include.proj.stats = TRUE, include.groups = TRUE, ... )
model |
A statistical model object. |
include.nobs |
Report the number of observations in the GOF block? |
include.rsquared |
Report R^2 in the GOF block? |
include.adjrs |
Report adjusted R^2 in the GOF block? |
include.fstatistic |
Report the F-statistic in the GOF block? |
include.proj.stats |
Include statistics for projected model in the GOF block? |
include.groups |
Report the number of groups? |
... |
Custom parameters, which are handed over to subroutines, in this
case to the |
Christoph Riedl, Claudia Zucca, Oliver Reiter, Philip Leifeld
extract method for fGARCH objectsextract method for fGARCH objects created by the
garchFit function in the fGarch package.
## S4 method for signature 'fGARCH' extract( model, include.nobs = TRUE, include.aic = TRUE, include.loglik = TRUE, ... )## S4 method for signature 'fGARCH' extract( model, include.nobs = TRUE, include.aic = TRUE, include.loglik = TRUE, ... )
model |
A statistical model object. |
include.nobs |
Report the number of observations in the GOF block? |
include.aic |
Report Akaike's Information Criterion (AIC) in the GOF block? |
include.loglik |
Report the log likelihood in the GOF block? |
... |
Custom parameters, which are handed over to subroutines. Currently not in use. |
extract method for fixest objectsextract method for fixest objects created by the
model fitting functions in the fixest package. The method can deal with
OLS (fitted by feols) and GLM/MLE models (fitted by
feglm and other functions).
## S4 method for signature 'fixest' extract( model, include.nobs = TRUE, include.groups = TRUE, include.rsquared = TRUE, include.adjrs = TRUE, include.proj.stats = TRUE, include.deviance = TRUE, include.loglik = TRUE, include.pseudors = TRUE, ... )## S4 method for signature 'fixest' extract( model, include.nobs = TRUE, include.groups = TRUE, include.rsquared = TRUE, include.adjrs = TRUE, include.proj.stats = TRUE, include.deviance = TRUE, include.loglik = TRUE, include.pseudors = TRUE, ... )
model |
A statistical model object. |
include.nobs |
Report the number of observations? |
include.groups |
Report the number of groups? |
include.rsquared |
Report R^2? (OLS only) |
include.adjrs |
Report adjusted R^2? (OLS only) |
include.proj.stats |
Include statistics for projected model? (OLS only) |
include.deviance |
Report the deviance? (GLM/MLE only) |
include.loglik |
Report the log likelihood? (GLM/MLE only) |
include.pseudors |
Report Pseudo-R^2? (GLM/MLE only) |
... |
Custom parameters, which are handed over to the
|
Christopher Poliquin, Philip Leifeld
extract method for forecast_ARIMA objectsextract method for forecast_ARIMA objects created by the
Arima function in the forecast package.
## S4 method for signature 'forecast_ARIMA' extract( model, include.pvalues = TRUE, include.aic = TRUE, include.aicc = TRUE, include.bic = TRUE, include.loglik = TRUE, include.nobs = TRUE, ... )## S4 method for signature 'forecast_ARIMA' extract( model, include.pvalues = TRUE, include.aic = TRUE, include.aicc = TRUE, include.bic = TRUE, include.loglik = TRUE, include.nobs = TRUE, ... )
model |
A statistical model object. |
include.pvalues |
Report p-values? |
include.aic |
Report Akaike's Information Criterion (AIC) in the GOF block? |
include.aicc |
Report AICC in the GOF block? |
include.bic |
Report the Bayesian Information Criterion (BIC) in the GOF block? |
include.loglik |
Report the log likelihood in the GOF block? |
include.nobs |
Report the number of observations in the GOF block? |
... |
Custom parameters, which are handed over to subroutines. Currently not in use. |
extract method for forecast objectsextract method for forecast objects created by the
forecast and holt functions
in the forecast package.
## S4 method for signature 'forecast' extract(model, ...)## S4 method for signature 'forecast' extract(model, ...)
model |
A statistical model object. |
... |
Custom parameters, which are handed over to subroutines. Currently not in use. |
extract method for gam objectsextract method for gam objects created by the
gam function in the mgcv package.
## S4 method for signature 'gam' extract( model, include.smooth = TRUE, include.aic = TRUE, include.bic = TRUE, include.loglik = TRUE, include.deviance = TRUE, include.dev.expl = TRUE, include.dispersion = TRUE, include.rsquared = TRUE, include.gcv = TRUE, include.nobs = TRUE, include.nsmooth = TRUE, ... )## S4 method for signature 'gam' extract( model, include.smooth = TRUE, include.aic = TRUE, include.bic = TRUE, include.loglik = TRUE, include.deviance = TRUE, include.dev.expl = TRUE, include.dispersion = TRUE, include.rsquared = TRUE, include.gcv = TRUE, include.nobs = TRUE, include.nsmooth = TRUE, ... )
model |
A statistical model object. |
include.smooth |
Report the smooth terms of a GAM? If they are reported, the EDF value is reported as the coefficient, and DF is included in parentheses (not standard errors because a chi-square test is used for the smooth terms). |
include.aic |
Report Akaike's Information Criterion (AIC) in the GOF block? |
include.bic |
Report the Bayesian Information Criterion (BIC) in the GOF block? |
include.loglik |
Report the log likelihood in the GOF block? |
include.deviance |
Report the deviance? |
include.dev.expl |
Report the deviance explained? |
include.dispersion |
Report the dispersion parameter? |
include.rsquared |
Report R^2 in the GOF block? |
include.gcv |
Report the GCV score? |
include.nobs |
Report the number of observations in the GOF block? |
include.nsmooth |
Report the number of smooth terms? |
... |
Custom parameters, which are handed over to subroutines, in this
case to the |
extract method for gamlss objectsextract method for gamlss objects created by the
gamlss function in the gamlss package.
## S4 method for signature 'gamlss' extract( model, robust = FALSE, include.nobs = TRUE, include.nagelkerke = TRUE, include.gaic = TRUE, ... )## S4 method for signature 'gamlss' extract( model, robust = FALSE, include.nobs = TRUE, include.nagelkerke = TRUE, include.gaic = TRUE, ... )
model |
A statistical model object. |
robust |
If TRUE computes robust standard errors in the variance-covariance matrix. |
include.nobs |
Report the number of observations in the GOF block? |
include.nagelkerke |
Report Nagelkerke R^2 in the GOF block? |
include.gaic |
Report Generalized Akaike's Information Criterion (AIC) in the GOF block? |
... |
Custom parameters, which are handed over to subroutines, in this
case to the |
extract method for gamlssZadj objectsextract method for gamlssZadj objects created by the
gamlssZadj function in the gamlss.inf
package.
## S4 method for signature 'gamlssZadj' extract( model, type = c("qr", "vcov"), include.nobs = TRUE, include.gaic = TRUE, ... )## S4 method for signature 'gamlssZadj' extract( model, type = c("qr", "vcov"), include.nobs = TRUE, include.gaic = TRUE, ... )
model |
A statistical model object. |
type |
The type. |
include.nobs |
Report the number of observations in the GOF block? |
include.gaic |
Report Generalized Akaike's Information Criterion (AIC) in the GOF block? |
... |
Custom parameters, which are handed over to subroutines, in this
case to the |
Ricardo Graiff Garcia, Philip Leifeld
extract method for gee objectsextract method for gee objects created by the
gee function in the gee package.
## S4 method for signature 'gee' extract(model, robust = TRUE, include.scale = TRUE, include.nobs = TRUE, ...)## S4 method for signature 'gee' extract(model, robust = TRUE, include.scale = TRUE, include.nobs = TRUE, ...)
model |
A statistical model object. |
robust |
If TRUE computes robust standard errors in the variance-covariance matrix. |
include.scale |
Report the dispersion or scale parameter? |
include.nobs |
Report the number of observations in the GOF block? |
... |
Custom parameters, which are handed over to subroutines, in this
case to the |
extract method for geeglm objectsextract method for geeglm objects created by the
geeglm function in the geepack package.
## S4 method for signature 'geeglm' extract( model, include.scale = TRUE, include.correlation = TRUE, include.nobs = TRUE, ... )## S4 method for signature 'geeglm' extract( model, include.scale = TRUE, include.correlation = TRUE, include.nobs = TRUE, ... )
model |
A statistical model object. |
include.scale |
Report the dispersion or scale parameter? |
include.correlation |
Report the correlation parameter alpha and its standard error? |
include.nobs |
Report the number of observations in the GOF block? |
... |
Custom parameters, which are handed over to subroutines. Currently not in use. |
extract method for gel objectsextract method for gel objects created by the
gel function in the gmm package.
## S4 method for signature 'gel' extract( model, include.obj.fcn = TRUE, include.overidentification = FALSE, include.nobs = TRUE, overIdentTest = c("LR", "LM", "J "), ... )## S4 method for signature 'gel' extract( model, include.obj.fcn = TRUE, include.overidentification = FALSE, include.nobs = TRUE, overIdentTest = c("LR", "LM", "J "), ... )
model |
A statistical model object. |
include.obj.fcn |
Report the value of the objective function
(= criterion function)? More precisely, this returns
|
include.overidentification |
Report the J-test for overidentification? |
include.nobs |
Report the number of observations in the GOF block? |
overIdentTest |
Which test statistics should be included in an overidentification test? |
... |
Custom parameters, which are handed over to subroutines, in this
case to the |
extract method for glm objectsextract method for glm objects created by the
glm function in the stats package.
## S4 method for signature 'glm' extract( model, include.aic = TRUE, include.bic = TRUE, include.loglik = TRUE, include.deviance = TRUE, include.nobs = TRUE, ... )## S4 method for signature 'glm' extract( model, include.aic = TRUE, include.bic = TRUE, include.loglik = TRUE, include.deviance = TRUE, include.nobs = TRUE, ... )
model |
A statistical model object. |
include.aic |
Report Akaike's Information Criterion (AIC) in the GOF block? |
include.bic |
Report the Bayesian Information Criterion (BIC) in the GOF block? |
include.loglik |
Report the log likelihood in the GOF block? |
include.deviance |
Report the deviance? |
include.nobs |
Report the number of observations in the GOF block? |
... |
Custom parameters, which are handed over to subroutines, in this
case to the |
extract method for glm.cluster objectsextract method for glm.cluster objects created by the
glm.cluster function in the miceadds package.
## S4 method for signature 'glm.cluster' extract( model, include.aic = TRUE, include.bic = TRUE, include.loglik = TRUE, include.deviance = TRUE, include.nobs = TRUE, ... )## S4 method for signature 'glm.cluster' extract( model, include.aic = TRUE, include.bic = TRUE, include.loglik = TRUE, include.deviance = TRUE, include.nobs = TRUE, ... )
model |
A statistical model object. |
include.aic |
Report Akaike's Information Criterion (AIC) in the GOF block? |
include.bic |
Report the Bayesian Information Criterion (BIC) in the GOF block? |
include.loglik |
Report the log likelihood in the GOF block? |
include.deviance |
Report the deviance? |
include.nobs |
Report the number of observations in the GOF block? |
... |
Custom parameters, which are handed over to subroutines. Currently not in use. |
Alexander Staudt, Philip Leifeld
extract method for glmerMod objectsextract method for glmerMod objects created by the
glmer function in the lme4 package.
## S4 method for signature 'glmerMod' extract( model, method = c("naive", "profile", "boot", "Wald"), level = 0.95, nsim = 1000, include.aic = TRUE, include.bic = TRUE, include.dic = FALSE, include.deviance = FALSE, include.loglik = TRUE, include.nobs = TRUE, include.groups = TRUE, include.variance = TRUE, ... )## S4 method for signature 'glmerMod' extract( model, method = c("naive", "profile", "boot", "Wald"), level = 0.95, nsim = 1000, include.aic = TRUE, include.bic = TRUE, include.dic = FALSE, include.deviance = FALSE, include.loglik = TRUE, include.nobs = TRUE, include.groups = TRUE, include.variance = TRUE, ... )
model |
A statistical model object. |
method |
The method used to compute confidence intervals or p-values.
The default value |
level |
Significance or confidence level ( |
nsim |
The MCMC sample size or number of bootstrapping replications on
the basis of which confidence intervals are computed (only if the
|
include.aic |
Report Akaike's Information Criterion (AIC) in the GOF block? |
include.bic |
Report the Bayesian Information Criterion (BIC) in the GOF block? |
include.dic |
Report the deviance information criterion (DIC)? |
include.deviance |
Report the deviance? |
include.loglik |
Report the log likelihood in the GOF block? |
include.nobs |
Report the number of observations in the GOF block? |
include.groups |
Report the number of groups? |
include.variance |
Report group variances? |
... |
Arguments to be passed to the |
extract method for glmmadmb objectsextract method for glmmadmb objects created by the
glmmadmb function in the glmmADMB package.
## S4 method for signature 'glmmadmb' extract( model, include.variance = TRUE, include.dispersion = TRUE, include.zero = TRUE, include.aic = TRUE, include.bic = TRUE, include.loglik = TRUE, include.nobs = TRUE, include.groups = TRUE, ... )## S4 method for signature 'glmmadmb' extract( model, include.variance = TRUE, include.dispersion = TRUE, include.zero = TRUE, include.aic = TRUE, include.bic = TRUE, include.loglik = TRUE, include.nobs = TRUE, include.groups = TRUE, ... )
model |
A statistical model object. |
include.variance |
Report group variances? |
include.dispersion |
Report the dispersion parameter? |
include.zero |
Should the binary part of a zero-inflated regression model or hurdle model be included in the coefficients block (after the count model)? |
include.aic |
Report Akaike's Information Criterion (AIC) in the GOF block? |
include.bic |
Report the Bayesian Information Criterion (BIC) in the GOF block? |
include.loglik |
Report the log likelihood in the GOF block? |
include.nobs |
Report the number of observations in the GOF block? |
include.groups |
Report the number of groups? |
... |
Custom parameters, which are handed over to subroutines. Currently not in use. |
extract method for glmmPQL objectsextract method for glmmPQL objects created by the
glmmPQL function in the MASS package.
## S4 method for signature 'glmmPQL' extract( model, include.aic = TRUE, include.bic = TRUE, include.loglik = TRUE, include.nobs = TRUE, include.groups = TRUE, include.variance = FALSE, ... )## S4 method for signature 'glmmPQL' extract( model, include.aic = TRUE, include.bic = TRUE, include.loglik = TRUE, include.nobs = TRUE, include.groups = TRUE, include.variance = FALSE, ... )
model |
A statistical model object. |
include.aic |
Report Akaike's Information Criterion (AIC) in the GOF block? |
include.bic |
Report the Bayesian Information Criterion (BIC) in the GOF block? |
include.loglik |
Report the log likelihood in the GOF block? |
include.nobs |
Report the number of observations in the GOF block? |
include.groups |
Report the number of groups? |
include.variance |
Report group variances? |
... |
Custom parameters, which are handed over to subroutines, in this
case to the |
extract method for glmmTMB objectsextract method for glmmTMB objects created by the
glmmTMB function in the glmmTMB package.
## S4 method for signature 'glmmTMB' extract( model, beside = FALSE, include.count = TRUE, include.zero = TRUE, include.aic = TRUE, include.groups = TRUE, include.variance = TRUE, include.loglik = TRUE, include.nobs = TRUE, ... )## S4 method for signature 'glmmTMB' extract( model, beside = FALSE, include.count = TRUE, include.zero = TRUE, include.aic = TRUE, include.groups = TRUE, include.variance = TRUE, include.loglik = TRUE, include.nobs = TRUE, ... )
model |
A statistical model object. |
beside |
Arrange the model terms below each other or beside each other? The binary model parameters and the count parameters can be displayed in two separate columns of the table. |
include.count |
Report the count parameters in the coefficients block (before the binary part for the zeros)? |
include.zero |
Should the binary part of the model be included in the coefficients block (after the count parameters)? |
include.aic |
Report Akaike's Information Criterion (AIC) in the GOF block? |
include.groups |
Report the number of groups? |
include.variance |
Report group variances? |
include.loglik |
Report the log likelihood in the GOF block? |
include.nobs |
Report the number of observations in the GOF block? |
... |
Custom parameters, which are handed over to subroutines, in this
case to the |
Ricardo Graiff Garcia, Philip Leifeld
extract method for glmrob objectsextract method for glmrob objects created by the
glmrob function in the robustbase package.
## S4 method for signature 'glmrob' extract(model, include.nobs = TRUE, ...)## S4 method for signature 'glmrob' extract(model, include.nobs = TRUE, ...)
model |
A statistical model object. |
include.nobs |
Report the number of observations in the GOF block? |
... |
Custom parameters, which are handed over to subroutines, in this
case to the |
extract method for gls objectsextract method for gls objects created by the
gls function in the nlme package.
## S4 method for signature 'gls' extract( model, include.aic = TRUE, include.bic = TRUE, include.loglik = TRUE, include.nobs = TRUE, ... )## S4 method for signature 'gls' extract( model, include.aic = TRUE, include.bic = TRUE, include.loglik = TRUE, include.nobs = TRUE, ... )
model |
A statistical model object. |
include.aic |
Report Akaike's Information Criterion (AIC) in the GOF block? |
include.bic |
Report the Bayesian Information Criterion (BIC) in the GOF block? |
include.loglik |
Report the log likelihood in the GOF block? |
include.nobs |
Report the number of observations in the GOF block? |
... |
Custom parameters, which are handed over to subroutines, in this
case to the |
extract method for gmm objectsextract method for gmm objects created by the
gmm function in the gmm package.
## S4 method for signature 'gmm' extract( model, include.obj.fcn = TRUE, include.overidentification = FALSE, include.nobs = TRUE, ... )## S4 method for signature 'gmm' extract( model, include.obj.fcn = TRUE, include.overidentification = FALSE, include.nobs = TRUE, ... )
model |
A statistical model object. |
include.obj.fcn |
Report the value of the objective function
(= criterion function)? More precisely, this returns
|
include.overidentification |
Report the J-test for overidentification? |
include.nobs |
Report the number of observations in the GOF block? |
... |
Custom parameters, which are handed over to subroutines, in this
case to the |
extract method for gnls objectsextract method for gnls objects created by the
gnls function in the nlme package.
## S4 method for signature 'gnls' extract( model, include.aic = TRUE, include.bic = TRUE, include.loglik = TRUE, include.nobs = TRUE, ... )## S4 method for signature 'gnls' extract( model, include.aic = TRUE, include.bic = TRUE, include.loglik = TRUE, include.nobs = TRUE, ... )
model |
A statistical model object. |
include.aic |
Report Akaike's Information Criterion (AIC) in the GOF block? |
include.bic |
Report the Bayesian Information Criterion (BIC) in the GOF block? |
include.loglik |
Report the log likelihood in the GOF block? |
include.nobs |
Report the number of observations in the GOF block? |
... |
Custom parameters, which are handed over to subroutines, in this
case to the |
extract method for gnm objectsextract method for gnm objects created by the
gnm function in the gnm package.
## S4 method for signature 'gnm' extract( model, include.aic = TRUE, include.bic = TRUE, include.loglik = TRUE, include.deviance = TRUE, include.nobs = TRUE, include.df = FALSE, include.chisq = FALSE, include.delta = FALSE, ... )## S4 method for signature 'gnm' extract( model, include.aic = TRUE, include.bic = TRUE, include.loglik = TRUE, include.deviance = TRUE, include.nobs = TRUE, include.df = FALSE, include.chisq = FALSE, include.delta = FALSE, ... )
model |
A statistical model object. |
include.aic |
Report Akaike's Information Criterion (AIC) in the GOF block? |
include.bic |
Report the Bayesian Information Criterion (BIC) in the GOF block? |
include.loglik |
Report the log likelihood in the GOF block? |
include.deviance |
Report the deviance? |
include.nobs |
Report the number of observations in the GOF block? |
include.df |
Report the degrees of freedom? |
include.chisq |
Report the chi squared statistic? |
include.delta |
Report the delta statistic? |
... |
Custom parameters, which are handed over to subroutines. Currently not in use. |
extract method for H2OBinomialModel objectsextract method for H2OBinomialModel objects created by
the h2o.glm function in the h2o package.
## S4 method for signature 'H2OBinomialModel' extract( model, standardized = FALSE, include.mse = TRUE, include.rsquared = TRUE, include.logloss = TRUE, include.meanerror = TRUE, include.auc = TRUE, include.gini = TRUE, include.deviance = TRUE, include.aic = TRUE, ... )## S4 method for signature 'H2OBinomialModel' extract( model, standardized = FALSE, include.mse = TRUE, include.rsquared = TRUE, include.logloss = TRUE, include.meanerror = TRUE, include.auc = TRUE, include.gini = TRUE, include.deviance = TRUE, include.aic = TRUE, ... )
model |
A statistical model object. |
standardized |
Report standardized coefficients instead of raw coefficients? |
include.mse |
Report the mean squared error in the GOF block? |
include.rsquared |
Report R^2 in the GOF block? |
include.logloss |
Report the log loss? |
include.meanerror |
Report the mean per-class error? |
include.auc |
Report the area under the curve (AUC)? |
include.gini |
Report the Gini coefficient? |
include.deviance |
Report the deviance? |
include.aic |
Report Akaike's Information Criterion (AIC) in the GOF block? |
... |
Custom parameters, which are handed over to subroutines. Currently not in use. |
extract method for hurdle objectsextract method for hurdle objects created by the
hurdle function in the pscl package.
## S4 method for signature 'hurdle' extract( model, beside = FALSE, include.count = TRUE, include.zero = TRUE, include.aic = TRUE, include.loglik = TRUE, include.nobs = TRUE, ... )## S4 method for signature 'hurdle' extract( model, beside = FALSE, include.count = TRUE, include.zero = TRUE, include.aic = TRUE, include.loglik = TRUE, include.nobs = TRUE, ... )
model |
A statistical model object. |
beside |
Arrange the model terms below each other or beside each other? The binary model parameters and the count parameters can be displayed in two separate columns of the table. |
include.count |
Report the count parameters in the coefficients block (before the binary part for the zeros)? |
include.zero |
Should the binary part of the model be included in the coefficients block (after the count parameters)? |
include.aic |
Report Akaike's Information Criterion (AIC) in the GOF block? |
include.loglik |
Report the log likelihood in the GOF block? |
include.nobs |
Report the number of observations in the GOF block? |
... |
Custom parameters, which are handed over to subroutines, in this
case to the |
extract method for ivreg objectsextract method for ivreg objects created by the
ivreg function in the AER package.
## S4 method for signature 'ivreg' extract( model, include.rsquared = TRUE, include.adjrs = TRUE, include.nobs = TRUE, include.fstatistic = FALSE, include.rmse = FALSE, ... )## S4 method for signature 'ivreg' extract( model, include.rsquared = TRUE, include.adjrs = TRUE, include.nobs = TRUE, include.fstatistic = FALSE, include.rmse = FALSE, ... )
model |
A statistical model object. |
include.rsquared |
Report R^2 in the GOF block? |
include.adjrs |
Report adjusted R^2 in the GOF block? |
include.nobs |
Report the number of observations in the GOF block? |
include.fstatistic |
Report the F-statistic in the GOF block? |
include.rmse |
Report the root mean square error (RMSE; = residual standard deviation) in the GOF block? |
... |
Custom parameters, which are handed over to subroutines, in this
case to the |
extract method for lm objectsextract method for lm objects created by the
lm function in the stats package.
## S4 method for signature 'lm' extract( model, include.rsquared = TRUE, include.adjrs = TRUE, include.nobs = TRUE, include.fstatistic = FALSE, include.rmse = FALSE, ... )## S4 method for signature 'lm' extract( model, include.rsquared = TRUE, include.adjrs = TRUE, include.nobs = TRUE, include.fstatistic = FALSE, include.rmse = FALSE, ... )
model |
A statistical model object. |
include.rsquared |
Report R^2 in the GOF block? |
include.adjrs |
Report adjusted R^2 in the GOF block? |
include.nobs |
Report the number of observations in the GOF block? |
include.fstatistic |
Report the F-statistic in the GOF block? |
include.rmse |
Report the root mean square error (RMSE; = residual standard deviation) in the GOF block? |
... |
Custom parameters, which are handed over to subroutines, in this
case to the |
extract method for lm.cluster objectsextract method for lm.cluster objects created by the
lm.cluster function in the miceadds package.
## S4 method for signature 'lm.cluster' extract( model, include.rsquared = TRUE, include.adjrs = TRUE, include.nobs = TRUE, include.fstatistic = FALSE, include.rmse = FALSE, ... )## S4 method for signature 'lm.cluster' extract( model, include.rsquared = TRUE, include.adjrs = TRUE, include.nobs = TRUE, include.fstatistic = FALSE, include.rmse = FALSE, ... )
model |
A statistical model object. |
include.rsquared |
Report R^2 in the GOF block? |
include.adjrs |
Report adjusted R^2 in the GOF block? |
include.nobs |
Report the number of observations in the GOF block? |
include.fstatistic |
Report the F-statistic in the GOF block? |
include.rmse |
Report the root mean square error (RMSE; = residual standard deviation) in the GOF block? |
... |
Custom parameters, which are handed over to subroutines. Currently not in use. |
Alexander Staudt, Philip Leifeld
extract method for lme objectsextract method for lme objects created by the
lme function in the nlme package.
## S4 method for signature 'lme' extract( model, include.aic = TRUE, include.bic = TRUE, include.loglik = TRUE, include.nobs = TRUE, include.groups = TRUE, include.variance = FALSE, ... )## S4 method for signature 'lme' extract( model, include.aic = TRUE, include.bic = TRUE, include.loglik = TRUE, include.nobs = TRUE, include.groups = TRUE, include.variance = FALSE, ... )
model |
A statistical model object. |
include.aic |
Report Akaike's Information Criterion (AIC) in the GOF block? |
include.bic |
Report the Bayesian Information Criterion (BIC) in the GOF block? |
include.loglik |
Report the log likelihood in the GOF block? |
include.nobs |
Report the number of observations in the GOF block? |
include.groups |
Report the number of groups? |
include.variance |
Report group variances? |
... |
Custom parameters, which are handed over to subroutines, in this
case to the |
extract method for lme4 objectsextract method for lme4 objects created by the
lme4 package.
## S4 method for signature 'lme4' extract( model, method = c("naive", "profile", "boot", "Wald"), level = 0.95, nsim = 1000, include.aic = TRUE, include.bic = TRUE, include.dic = FALSE, include.deviance = FALSE, include.loglik = TRUE, include.nobs = TRUE, include.groups = TRUE, include.variance = TRUE, ... )## S4 method for signature 'lme4' extract( model, method = c("naive", "profile", "boot", "Wald"), level = 0.95, nsim = 1000, include.aic = TRUE, include.bic = TRUE, include.dic = FALSE, include.deviance = FALSE, include.loglik = TRUE, include.nobs = TRUE, include.groups = TRUE, include.variance = TRUE, ... )
model |
A statistical model object. |
method |
The method used to compute confidence intervals or p-values.
The default value |
level |
Significance or confidence level ( |
nsim |
The MCMC sample size or number of bootstrapping replications on
the basis of which confidence intervals are computed (only if the
|
include.aic |
Report Akaike's Information Criterion (AIC) in the GOF block? |
include.bic |
Report the Bayesian Information Criterion (BIC) in the GOF block? |
include.dic |
Report the deviance information criterion (DIC)? |
include.deviance |
Report the deviance? |
include.loglik |
Report the log likelihood in the GOF block? |
include.nobs |
Report the number of observations in the GOF block? |
include.groups |
Report the number of groups? |
include.variance |
Report group variances? |
... |
Arguments to be passed to the |
extract method for lmerMod objectsextract method for lmerMod objects created by the
lmer function in the lme4 package.
## S4 method for signature 'lmerMod' extract( model, method = c("naive", "profile", "boot", "Wald"), level = 0.95, nsim = 1000, include.aic = TRUE, include.bic = TRUE, include.dic = FALSE, include.deviance = FALSE, include.loglik = TRUE, include.nobs = TRUE, include.groups = TRUE, include.variance = TRUE, ... )## S4 method for signature 'lmerMod' extract( model, method = c("naive", "profile", "boot", "Wald"), level = 0.95, nsim = 1000, include.aic = TRUE, include.bic = TRUE, include.dic = FALSE, include.deviance = FALSE, include.loglik = TRUE, include.nobs = TRUE, include.groups = TRUE, include.variance = TRUE, ... )
model |
A statistical model object. |
method |
The method used to compute confidence intervals or p-values.
The default value |
level |
Significance or confidence level ( |
nsim |
The MCMC sample size or number of bootstrapping replications on
the basis of which confidence intervals are computed (only if the
|
include.aic |
Report Akaike's Information Criterion (AIC) in the GOF block? |
include.bic |
Report the Bayesian Information Criterion (BIC) in the GOF block? |
include.dic |
Report the deviance information criterion (DIC)? |
include.deviance |
Report the deviance? |
include.loglik |
Report the log likelihood in the GOF block? |
include.nobs |
Report the number of observations in the GOF block? |
include.groups |
Report the number of groups? |
include.variance |
Report group variances? |
... |
Arguments to be passed to the |
extract method for lmrob objectsextract method for lmrob objects created by the
lmrob function in the robustbase package.
extract method for lmRob objects created by the
lmRob function in the robust package.
## S4 method for signature 'lmrob' extract(model, include.nobs = TRUE, ...) ## S4 method for signature 'lmRob' extract( model, include.rsquared = TRUE, include.nobs = TRUE, include.rmse = TRUE, ... )## S4 method for signature 'lmrob' extract(model, include.nobs = TRUE, ...) ## S4 method for signature 'lmRob' extract( model, include.rsquared = TRUE, include.nobs = TRUE, include.rmse = TRUE, ... )
model |
A statistical model object. |
include.nobs |
Report the number of observations in the GOF block? |
... |
Custom parameters, which are handed over to subroutines, in this
case to the |
include.rsquared |
Report R^2 in the GOF block? |
include.rmse |
Report the root mean square error (RMSE; = residual standard deviation) in the GOF block? |
extract method for lnam objectsextract method for lnam objects created by the
lnam function in the sna package.
## S4 method for signature 'lnam' extract( model, include.rsquared = TRUE, include.adjrs = TRUE, include.aic = TRUE, include.bic = TRUE, include.loglik = TRUE, ... )## S4 method for signature 'lnam' extract( model, include.rsquared = TRUE, include.adjrs = TRUE, include.aic = TRUE, include.bic = TRUE, include.loglik = TRUE, ... )
model |
A statistical model object. |
include.rsquared |
Report R^2 in the GOF block? |
include.adjrs |
Report adjusted R^2 in the GOF block? |
include.aic |
Report Akaike's Information Criterion (AIC) in the GOF block? |
include.bic |
Report the Bayesian Information Criterion (BIC) in the GOF block? |
include.loglik |
Report the log likelihood in the GOF block? |
... |
Custom parameters, which are handed over to subroutines, in this
case to the |
extract method for logitmfx objectsextract method for logitmfx objects created by the
logitmfx function in the mfx package.
## S4 method for signature 'logitmfx' extract( model, include.nobs = TRUE, include.loglik = TRUE, include.deviance = TRUE, include.aic = TRUE, include.bic = TRUE, ... )## S4 method for signature 'logitmfx' extract( model, include.nobs = TRUE, include.loglik = TRUE, include.deviance = TRUE, include.aic = TRUE, include.bic = TRUE, ... )
model |
A statistical model object. |
include.nobs |
Report the number of observations in the GOF block? |
include.loglik |
Report the log likelihood in the GOF block? |
include.deviance |
Report the deviance? |
include.aic |
Report Akaike's Information Criterion (AIC) in the GOF block? |
include.bic |
Report the Bayesian Information Criterion (BIC) in the GOF block? |
... |
Custom parameters, which are handed over to subroutines. Currently not in use. |
extract method for logitor objectsextract method for logitor objects created by the
logitor function in the mfx package.
## S4 method for signature 'logitor' extract( model, include.nobs = TRUE, include.loglik = TRUE, include.deviance = TRUE, include.aic = TRUE, include.bic = TRUE, ... )## S4 method for signature 'logitor' extract( model, include.nobs = TRUE, include.loglik = TRUE, include.deviance = TRUE, include.aic = TRUE, include.bic = TRUE, ... )
model |
A statistical model object. |
include.nobs |
Report the number of observations in the GOF block? |
include.loglik |
Report the log likelihood in the GOF block? |
include.deviance |
Report the deviance? |
include.aic |
Report Akaike's Information Criterion (AIC) in the GOF block? |
include.bic |
Report the Bayesian Information Criterion (BIC) in the GOF block? |
... |
Custom parameters, which are handed over to subroutines. Currently not in use. |
extract method for logitr objectsextract method for logitr objects created by the
logitr function in the logitr package.
## S4 method for signature 'logitr' extract( model, include.nobs = TRUE, include.loglik = TRUE, include.aic = TRUE, include.bic = TRUE, ... )## S4 method for signature 'logitr' extract( model, include.nobs = TRUE, include.loglik = TRUE, include.aic = TRUE, include.bic = TRUE, ... )
model |
A statistical model object. |
include.nobs |
Include the number of observations in summary table? |
include.loglik |
Include the log-likelihood in summary table? |
include.aic |
Include the the AIC in summary table? |
include.bic |
Include the the BIC in summary table? |
... |
Custom parameters, which are handed over to subroutines. Currently not in use. |
John Paul Helveston, [email protected]
extract method for lqmm objectsextract method for lqmm objects created by the
lqmm function in the lqmm package.
## S4 method for signature 'lqmm' extract( model, include.aic = TRUE, include.bic = TRUE, include.loglik = TRUE, include.nobs = TRUE, include.groups = TRUE, include.tau = FALSE, use.ci = FALSE, beside = TRUE, ... )## S4 method for signature 'lqmm' extract( model, include.aic = TRUE, include.bic = TRUE, include.loglik = TRUE, include.nobs = TRUE, include.groups = TRUE, include.tau = FALSE, use.ci = FALSE, beside = TRUE, ... )
model |
A statistical model object. |
include.aic |
Report Akaike's Information Criterion (AIC) in the GOF block? |
include.bic |
Report the Bayesian Information Criterion (BIC) in the GOF block? |
include.loglik |
Report the log likelihood in the GOF block? |
include.nobs |
Report the number of observations in the GOF block? |
include.groups |
Report the number of groups? |
include.tau |
Report tau? |
use.ci |
Report confidence intervals in the GOF block? |
beside |
Arrange the model terms below each other or beside each other? |
... |
Custom parameters, which are handed over to subroutines, in this
case to the |
extract method for lrm objectsextract method for lrm objects created by the
lrm function in the rms package.
## S4 method for signature 'lrm' extract( model, include.pseudors = TRUE, include.lr = TRUE, include.nobs = TRUE, ... )## S4 method for signature 'lrm' extract( model, include.pseudors = TRUE, include.lr = TRUE, include.nobs = TRUE, ... )
model |
A statistical model object. |
include.pseudors |
Report pseudo R^2 in the GOF block? |
include.lr |
Report likelihood ratio test? |
include.nobs |
Report the number of observations in the GOF block? |
... |
Custom parameters, which are handed over to subroutines. Currently not in use. |
Fabrice Le Lec
extract method for maxLik objectsextract method for maxLik objects created by the
maxLik function in the maxLik package.
## S4 method for signature 'maxLik' extract(model, include.loglik = TRUE, include.aic = TRUE, ...)## S4 method for signature 'maxLik' extract(model, include.loglik = TRUE, include.aic = TRUE, ...)
model |
A statistical model object. |
include.loglik |
Report the log likelihood in the GOF block? |
include.aic |
Report the AIC in the GOF block? |
... |
Custom parameters, which are handed over to subroutines, in this
case to the |
extract method for merMod objectsextract method for merMod objects created by the
lme4 package.
## S4 method for signature 'merMod' extract( model, method = c("naive", "profile", "boot", "Wald"), level = 0.95, nsim = 1000, include.aic = TRUE, include.bic = TRUE, include.dic = FALSE, include.deviance = FALSE, include.loglik = TRUE, include.nobs = TRUE, include.groups = TRUE, include.variance = TRUE, ... )## S4 method for signature 'merMod' extract( model, method = c("naive", "profile", "boot", "Wald"), level = 0.95, nsim = 1000, include.aic = TRUE, include.bic = TRUE, include.dic = FALSE, include.deviance = FALSE, include.loglik = TRUE, include.nobs = TRUE, include.groups = TRUE, include.variance = TRUE, ... )
model |
A statistical model object. |
method |
The method used to compute confidence intervals or p-values.
The default value |
level |
Significance or confidence level ( |
nsim |
The MCMC sample size or number of bootstrapping replications on
the basis of which confidence intervals are computed (only if the
|
include.aic |
Report Akaike's Information Criterion (AIC) in the GOF block? |
include.bic |
Report the Bayesian Information Criterion (BIC) in the GOF block? |
include.dic |
Report the deviance information criterion (DIC)? |
include.deviance |
Report the deviance? |
include.loglik |
Report the log likelihood in the GOF block? |
include.nobs |
Report the number of observations in the GOF block? |
include.groups |
Report the number of groups? |
include.variance |
Report group variances? |
... |
Arguments to be passed to the |
extract method for mhurdle objectsextract method for mhurdle objects created by the
mhurdle function in the mhurdle package.
## S4 method for signature 'mhurdle' extract(model, include.nobs = TRUE, include.loglik = TRUE, ...)## S4 method for signature 'mhurdle' extract(model, include.nobs = TRUE, include.loglik = TRUE, ...)
model |
A statistical model object. |
include.nobs |
Report the number of observations in the GOF block? |
include.loglik |
Report the log likelihood in the GOF block? |
... |
Custom parameters, which are handed over to subroutines, in this
case to the |
extract method for mlogit objectsextract method for mlogit objects created by the
mlogit function in the mlogit package.
## S4 method for signature 'mlogit' extract( model, include.aic = TRUE, include.loglik = TRUE, include.nobs = TRUE, include.groups = TRUE, include.order = FALSE, include.iterations = FALSE, beside = FALSE, ... )## S4 method for signature 'mlogit' extract( model, include.aic = TRUE, include.loglik = TRUE, include.nobs = TRUE, include.groups = TRUE, include.order = FALSE, include.iterations = FALSE, beside = FALSE, ... )
model |
A statistical model object. |
include.aic |
Report Akaike's Information Criterion (AIC) in the GOF block? |
include.loglik |
Report the log likelihood in the GOF block? |
include.nobs |
Report the number of observations in the GOF block? |
include.groups |
Report the number of groups? |
include.order |
Report coefficient names in alphabetical order? |
include.iterations |
Report the number of iterations? |
beside |
Arrange the model terms below each other or beside each other? |
... |
Custom parameters, which are handed over to subroutines, in this
case to the |
extract method for model.selection objectsextract method for model.selection objects created by
the model.sel and dredge functions
in the MuMIn package.
## S4 method for signature 'model.selection' extract( model, include.loglik = TRUE, include.aicc = TRUE, include.delta = TRUE, include.weight = TRUE, include.nobs = TRUE, ... )## S4 method for signature 'model.selection' extract( model, include.loglik = TRUE, include.aicc = TRUE, include.delta = TRUE, include.weight = TRUE, include.nobs = TRUE, ... )
model |
A statistical model object. |
include.loglik |
Report the log likelihood in the GOF block? |
include.aicc |
Report AICC in the GOF block? |
include.delta |
Report the delta statistic? |
include.weight |
Report Akaike weights? |
include.nobs |
Report the number of observations in the GOF block? |
... |
Custom parameters, which are handed over to subroutines. Currently not in use. |
extract method for mtergm objectsextract method for mtergm objects created by the
mtergm function in the btergm package.
## S4 method for signature 'mtergm' extract( model, include.nobs = TRUE, include.aic = TRUE, include.bic = TRUE, include.loglik = TRUE, ... )## S4 method for signature 'mtergm' extract( model, include.nobs = TRUE, include.aic = TRUE, include.bic = TRUE, include.loglik = TRUE, ... )
model |
A statistical model object. |
include.nobs |
Report the number of observations in the GOF block? |
include.aic |
Report Akaike's Information Criterion (AIC) in the GOF block? |
include.bic |
Report the Bayesian Information Criterion (BIC) in the GOF block? |
include.loglik |
Report the log likelihood in the GOF block? |
... |
Custom parameters, which are handed over to subroutines. Currently not in use. |
extract method for multinom objectsextract method for multinom objects created by the
multinom function in the nnet package.
## S4 method for signature 'multinom' extract( model, include.pvalues = TRUE, include.aic = TRUE, include.bic = TRUE, include.loglik = TRUE, include.deviance = TRUE, include.nobs = TRUE, include.groups = TRUE, levels = model$lev, beside = FALSE, ... )## S4 method for signature 'multinom' extract( model, include.pvalues = TRUE, include.aic = TRUE, include.bic = TRUE, include.loglik = TRUE, include.deviance = TRUE, include.nobs = TRUE, include.groups = TRUE, levels = model$lev, beside = FALSE, ... )
model |
A statistical model object. |
include.pvalues |
Report p-values? |
include.aic |
Report Akaike's Information Criterion (AIC) in the GOF block? |
include.bic |
Report the Bayesian Information Criterion (BIC) in the GOF block? |
include.loglik |
Report the log likelihood in the GOF block? |
include.deviance |
Report the deviance? |
include.nobs |
Report the number of observations in the GOF block? |
include.groups |
Report the number of groups? |
levels |
The names of the levels of a multinomial model that should be included in the table. Should be provided as a vector of character strings. |
beside |
Arrange the model terms below each other or beside each other? |
... |
Custom parameters, which are handed over to subroutines, in this
case to the |
extract method for negbin objectsextract method for negbin objects created by the
glm.nb function in the MASS package.
## S4 method for signature 'negbin' extract( model, include.aic = TRUE, include.bic = TRUE, include.loglik = TRUE, include.deviance = TRUE, include.nobs = TRUE, ... )## S4 method for signature 'negbin' extract( model, include.aic = TRUE, include.bic = TRUE, include.loglik = TRUE, include.deviance = TRUE, include.nobs = TRUE, ... )
model |
A statistical model object. |
include.aic |
Report Akaike's Information Criterion (AIC) in the GOF block? |
include.bic |
Report the Bayesian Information Criterion (BIC) in the GOF block? |
include.loglik |
Report the log likelihood in the GOF block? |
include.deviance |
Report the deviance? |
include.nobs |
Report the number of observations in the GOF block? |
... |
Custom parameters, which are handed over to subroutines, in this
case to the |
extract method for negbinirr objectsextract method for negbinirr objects created by the
negbinirr function in the mfx package.
## S4 method for signature 'negbinirr' extract( model, include.nobs = TRUE, include.loglik = TRUE, include.deviance = TRUE, include.aic = TRUE, include.bic = TRUE, ... )## S4 method for signature 'negbinirr' extract( model, include.nobs = TRUE, include.loglik = TRUE, include.deviance = TRUE, include.aic = TRUE, include.bic = TRUE, ... )
model |
A statistical model object. |
include.nobs |
Report the number of observations in the GOF block? |
include.loglik |
Report the log likelihood in the GOF block? |
include.deviance |
Report the deviance? |
include.aic |
Report Akaike's Information Criterion (AIC) in the GOF block? |
include.bic |
Report the Bayesian Information Criterion (BIC) in the GOF block? |
... |
Custom parameters, which are handed over to subroutines. Currently not in use. |
extract method for negbinmfx objectsextract method for negbinmfx objects created by the
negbinmfx function in the mfx package.
## S4 method for signature 'negbinmfx' extract( model, include.nobs = TRUE, include.loglik = TRUE, include.deviance = TRUE, include.aic = TRUE, include.bic = TRUE, ... )## S4 method for signature 'negbinmfx' extract( model, include.nobs = TRUE, include.loglik = TRUE, include.deviance = TRUE, include.aic = TRUE, include.bic = TRUE, ... )
model |
A statistical model object. |
include.nobs |
Report the number of observations in the GOF block? |
include.loglik |
Report the log likelihood in the GOF block? |
include.deviance |
Report the deviance? |
include.aic |
Report Akaike's Information Criterion (AIC) in the GOF block? |
include.bic |
Report the Bayesian Information Criterion (BIC) in the GOF block? |
... |
Custom parameters, which are handed over to subroutines. Currently not in use. |
extract method for netlogit objectsextract method for netlogit objects created by the
netlogit function in the sna package.
## S4 method for signature 'netlogit' extract( model, include.aic = TRUE, include.bic = TRUE, include.deviance = TRUE, include.nobs = TRUE, ... )## S4 method for signature 'netlogit' extract( model, include.aic = TRUE, include.bic = TRUE, include.deviance = TRUE, include.nobs = TRUE, ... )
model |
A statistical model object. |
include.aic |
Report Akaike's Information Criterion (AIC) in the GOF block? |
include.bic |
Report the Bayesian Information Criterion (BIC) in the GOF block? |
include.deviance |
Report the deviance? |
include.nobs |
Report the number of observations in the GOF block? |
... |
Custom parameters, which are handed over to subroutines. Currently not in use. |
extract method for nlme objectsextract method for nlme objects created by the
nlme function in the nlme package.
## S4 method for signature 'nlme' extract( model, include.aic = TRUE, include.bic = TRUE, include.loglik = TRUE, include.nobs = TRUE, include.groups = TRUE, include.variance = FALSE, ... )## S4 method for signature 'nlme' extract( model, include.aic = TRUE, include.bic = TRUE, include.loglik = TRUE, include.nobs = TRUE, include.groups = TRUE, include.variance = FALSE, ... )
model |
A statistical model object. |
include.aic |
Report Akaike's Information Criterion (AIC) in the GOF block? |
include.bic |
Report the Bayesian Information Criterion (BIC) in the GOF block? |
include.loglik |
Report the log likelihood in the GOF block? |
include.nobs |
Report the number of observations in the GOF block? |
include.groups |
Report the number of groups? |
include.variance |
Report group variances? |
... |
Custom parameters, which are handed over to subroutines, in this
case to the |
extract method for nlmerMod objectsextract method for nlmerMod objects created by the
nlmer function in the lme4 package.
## S4 method for signature 'nlmerMod' extract( model, method = c("naive", "profile", "boot", "Wald"), level = 0.95, nsim = 1000, include.aic = TRUE, include.bic = TRUE, include.dic = FALSE, include.deviance = FALSE, include.loglik = TRUE, include.nobs = TRUE, include.groups = TRUE, include.variance = TRUE, ... )## S4 method for signature 'nlmerMod' extract( model, method = c("naive", "profile", "boot", "Wald"), level = 0.95, nsim = 1000, include.aic = TRUE, include.bic = TRUE, include.dic = FALSE, include.deviance = FALSE, include.loglik = TRUE, include.nobs = TRUE, include.groups = TRUE, include.variance = TRUE, ... )
model |
A statistical model object. |
method |
The method used to compute confidence intervals or p-values.
The default value |
level |
Significance or confidence level ( |
nsim |
The MCMC sample size or number of bootstrapping replications on
the basis of which confidence intervals are computed (only if the
|
include.aic |
Report Akaike's Information Criterion (AIC) in the GOF block? |
include.bic |
Report the Bayesian Information Criterion (BIC) in the GOF block? |
include.dic |
Report the deviance information criterion (DIC)? |
include.deviance |
Report the deviance? |
include.loglik |
Report the log likelihood in the GOF block? |
include.nobs |
Report the number of observations in the GOF block? |
include.groups |
Report the number of groups? |
include.variance |
Report group variances? |
... |
Arguments to be passed to the |
extract method for oglmx objectsextract method for oglmx objects created by the
oglmx function in the oglmx package.
## S4 method for signature 'oglmx' extract( model, include.aic = TRUE, include.iterations = TRUE, include.loglik = TRUE, include.nobs = TRUE, include.rsquared = TRUE, ... )## S4 method for signature 'oglmx' extract( model, include.aic = TRUE, include.iterations = TRUE, include.loglik = TRUE, include.nobs = TRUE, include.rsquared = TRUE, ... )
model |
A statistical model object. |
include.aic |
Report Akaike's Information Criterion (AIC) in the GOF block? |
include.iterations |
Report the number of iterations? |
include.loglik |
Report the log likelihood in the GOF block? |
include.nobs |
Report the number of observations in the GOF block? |
include.rsquared |
Report R^2 in the GOF block? |
... |
Custom parameters, which are handed over to subroutines, in this
case to the |
extract method for ols objectsextract method for ols objects created by the
ols function in the rms package.
## S4 method for signature 'ols' extract( model, include.nobs = TRUE, include.rsquared = TRUE, include.adjrs = TRUE, include.fstatistic = FALSE, include.lr = TRUE, ... )## S4 method for signature 'ols' extract( model, include.nobs = TRUE, include.rsquared = TRUE, include.adjrs = TRUE, include.fstatistic = FALSE, include.lr = TRUE, ... )
model |
A statistical model object. |
include.nobs |
Report the number of observations in the GOF block? |
include.rsquared |
Report R^2 in the GOF block? |
include.adjrs |
Report adjusted R^2 in the GOF block? |
include.fstatistic |
Report the F-statistic in the GOF block? |
include.lr |
Report likelihood ratio test? |
... |
Custom parameters, which are handed over to subroutines. Currently not in use. |
extract method for pcce objectsextract method for pcce objects created by the
pcce function in the plm package.
## S4 method for signature 'pcce' extract( model, include.r.squared = TRUE, include.sumsquares = TRUE, include.nobs = TRUE, ... )## S4 method for signature 'pcce' extract( model, include.r.squared = TRUE, include.sumsquares = TRUE, include.nobs = TRUE, ... )
model |
A statistical model object. |
include.r.squared |
Report the HPY R-squared statistic in the GOF block? |
include.sumsquares |
Report the total and residual sum of squares in the GOF block? |
include.nobs |
Report the number of observations in the GOF block? |
... |
Custom parameters, which are handed over to subroutines, in this
case to the |
extract method for pglm objectsextract method for pglm objects created by the
pglm function in the pglm package.
## S4 method for signature 'pglm' extract( model, include.aic = TRUE, include.loglik = TRUE, include.nobs = TRUE, ... )## S4 method for signature 'pglm' extract( model, include.aic = TRUE, include.loglik = TRUE, include.nobs = TRUE, ... )
model |
A statistical model object. |
include.aic |
Report Akaike's Information Criterion (AIC) in the GOF block? |
include.loglik |
Report the log likelihood in the GOF block? |
include.nobs |
Report the number of observations in the GOF block? |
... |
Custom parameters, which are handed over to subroutines, in this
case to the |
extract method for pgmm objectsextract method for pgmm objects created by the
pgmm function in the plm package.
## S4 method for signature 'pgmm' extract( model, include.nobs = TRUE, include.sargan = TRUE, include.wald = TRUE, ... )## S4 method for signature 'pgmm' extract( model, include.nobs = TRUE, include.sargan = TRUE, include.wald = TRUE, ... )
model |
A statistical model object. |
include.nobs |
Report the number of observations in the GOF block? |
include.sargan |
Report the Sargan test? |
include.wald |
Report the Wald statistic? |
... |
Custom parameters, which are handed over to subroutines, in this
case to the |
extract method for phreg objectsextract method for phreg objects created by the
phreg function in the eha package.
## S4 method for signature 'phreg' extract( model, include.aic = TRUE, include.loglik = TRUE, include.lr = TRUE, include.nobs = TRUE, include.events = TRUE, include.trisk = TRUE, ... )## S4 method for signature 'phreg' extract( model, include.aic = TRUE, include.loglik = TRUE, include.lr = TRUE, include.nobs = TRUE, include.events = TRUE, include.trisk = TRUE, ... )
model |
A statistical model object. |
include.aic |
Report Akaike's Information Criterion (AIC) in the GOF block? |
include.loglik |
Report the log likelihood in the GOF block? |
include.lr |
Report likelihood ratio test? |
include.nobs |
Report the number of observations in the GOF block? |
include.events |
Report the number of events in the GOF block? |
include.trisk |
Report the total time at risk (in event-history models)? |
... |
Custom parameters, which are handed over to subroutines. Currently not in use. |
extract method for plm objectsextract method for plm objects created by the
plm function in the plm package.
## S4 method for signature 'plm' extract( model, include.rsquared = TRUE, include.adjrs = TRUE, include.nobs = TRUE, include.variance = TRUE, ... )## S4 method for signature 'plm' extract( model, include.rsquared = TRUE, include.adjrs = TRUE, include.nobs = TRUE, include.variance = TRUE, ... )
model |
A statistical model object. |
include.rsquared |
Report R^2 in the GOF block? |
include.adjrs |
Report adjusted R^2 in the GOF block? |
include.nobs |
Report the number of observations in the GOF block? |
include.variance |
Report group variances? |
... |
Custom parameters, which are handed over to subroutines, in this
case to the |
extract method for pmg objectsextract method for pmg objects created by the
pmg function in the plm package.
## S4 method for signature 'pmg' extract(model, include.nobs = TRUE, ...)## S4 method for signature 'pmg' extract(model, include.nobs = TRUE, ...)
model |
A statistical model object. |
include.nobs |
Report the number of observations in the GOF block? |
... |
Custom parameters, which are handed over to subroutines, in this
case to the |
extract method for poissonirr objectsextract method for poissonirr objects created by the
poissonirr function in the mfx package.
## S4 method for signature 'poissonirr' extract( model, include.nobs = TRUE, include.loglik = TRUE, include.deviance = TRUE, include.aic = TRUE, include.bic = TRUE, ... )## S4 method for signature 'poissonirr' extract( model, include.nobs = TRUE, include.loglik = TRUE, include.deviance = TRUE, include.aic = TRUE, include.bic = TRUE, ... )
model |
A statistical model object. |
include.nobs |
Report the number of observations in the GOF block? |
include.loglik |
Report the log likelihood in the GOF block? |
include.deviance |
Report the deviance? |
include.aic |
Report Akaike's Information Criterion (AIC) in the GOF block? |
include.bic |
Report the Bayesian Information Criterion (BIC) in the GOF block? |
... |
Custom parameters, which are handed over to subroutines. Currently not in use. |
extract method for poissonmfx objectsextract method for poissonmfx objects created by the
poissonmfx function in the mfx package.
## S4 method for signature 'poissonmfx' extract( model, include.nobs = TRUE, include.loglik = TRUE, include.deviance = TRUE, include.aic = TRUE, include.bic = TRUE, ... )## S4 method for signature 'poissonmfx' extract( model, include.nobs = TRUE, include.loglik = TRUE, include.deviance = TRUE, include.aic = TRUE, include.bic = TRUE, ... )
model |
A statistical model object. |
include.nobs |
Report the number of observations in the GOF block? |
include.loglik |
Report the log likelihood in the GOF block? |
include.deviance |
Report the deviance? |
include.aic |
Report Akaike's Information Criterion (AIC) in the GOF block? |
include.bic |
Report the Bayesian Information Criterion (BIC) in the GOF block? |
... |
Custom parameters, which are handed over to subroutines. Currently not in use. |
extract method for polr objectsextract method for polr objects created by the
polr function in the MASS package.
## S4 method for signature 'polr' extract( model, include.thresholds = TRUE, include.aic = TRUE, include.bic = TRUE, include.loglik = TRUE, include.deviance = TRUE, include.nobs = TRUE, ... )## S4 method for signature 'polr' extract( model, include.thresholds = TRUE, include.aic = TRUE, include.bic = TRUE, include.loglik = TRUE, include.deviance = TRUE, include.nobs = TRUE, ... )
model |
A statistical model object. |
include.thresholds |
Report thresholds in the GOF block? |
include.aic |
Report Akaike's Information Criterion (AIC) in the GOF block? |
include.bic |
Report the Bayesian Information Criterion (BIC) in the GOF block? |
include.loglik |
Report the log likelihood in the GOF block? |
include.deviance |
Report the deviance? |
include.nobs |
Report the number of observations in the GOF block? |
... |
Custom parameters, which are handed over to subroutines, in this
case to the |
extract method for probitmfx objectsextract method for probitmfx objects created by the
probitmfx function in the mfx package.
## S4 method for signature 'probitmfx' extract( model, include.nobs = TRUE, include.loglik = TRUE, include.deviance = TRUE, include.aic = TRUE, include.bic = TRUE, ... )## S4 method for signature 'probitmfx' extract( model, include.nobs = TRUE, include.loglik = TRUE, include.deviance = TRUE, include.aic = TRUE, include.bic = TRUE, ... )
model |
A statistical model object. |
include.nobs |
Report the number of observations in the GOF block? |
include.loglik |
Report the log likelihood in the GOF block? |
include.deviance |
Report the deviance? |
include.aic |
Report Akaike's Information Criterion (AIC) in the GOF block? |
include.bic |
Report the Bayesian Information Criterion (BIC) in the GOF block? |
... |
Custom parameters, which are handed over to subroutines. Currently not in use. |
extract method for rem.dyad objectsextract method for rem.dyad objects created by the
rem.dyad function in the relevent package.
## S4 method for signature 'rem.dyad' extract( model, include.nvertices = TRUE, include.events = TRUE, include.aic = TRUE, include.aicc = TRUE, include.bic = TRUE, ... )## S4 method for signature 'rem.dyad' extract( model, include.nvertices = TRUE, include.events = TRUE, include.aic = TRUE, include.aicc = TRUE, include.bic = TRUE, ... )
model |
A statistical model object. |
include.nvertices |
Report the number of vertices in a STERGM? |
include.events |
Report the number of events in the GOF block? |
include.aic |
Report Akaike's Information Criterion (AIC) in the GOF block? |
include.aicc |
Report AICC in the GOF block? |
include.bic |
Report the Bayesian Information Criterion (BIC) in the GOF block? |
... |
Custom parameters, which are handed over to subroutines. Currently not in use. |
extract method for remstimate objectsextract method for remstimate objects created by the
remstimate function in the remstimate
package.
## S4 method for signature 'remstimate' extract( model, include.nobs = TRUE, include.aic = TRUE, include.aicc = TRUE, include.bic = TRUE, include.loglik = TRUE, post.mean = FALSE, ... )## S4 method for signature 'remstimate' extract( model, include.nobs = TRUE, include.aic = TRUE, include.aicc = TRUE, include.bic = TRUE, include.loglik = TRUE, post.mean = FALSE, ... )
model |
A statistical model object. |
include.nobs |
Report the number of observations in the GOF block? |
include.aic |
Report Akaike's Information Criterion (AIC) in the GOF block? |
include.aicc |
Report Corrected Akaike's Information Criterion (AICc) in the GOF block? |
include.bic |
Report the Bayesian Information Criterion (BIC) in the GOF block? |
include.loglik |
Report the log likelihood in the GOF block? |
post.mean |
Report the posterior means, rather than the posterior modes, as coefficients? |
... |
Custom parameters, which are handed over to subroutines. Currently not in use. |
extract method for rlm objectsextract method for rlm objects created by the
rlm function in the MASS package.
## S4 method for signature 'rlm' extract(model, include.nobs = TRUE, ...)## S4 method for signature 'rlm' extract(model, include.nobs = TRUE, ...)
model |
A statistical model object. |
include.nobs |
Report the number of observations in the GOF block? |
... |
Custom parameters, which are handed over to subroutines, in this
case to the |
extract method for rq objectsextract method for rq objects created by the
rq function in the quantreg package.
## S4 method for signature 'rq' extract(model, include.nobs = TRUE, include.percentile = TRUE, ...)## S4 method for signature 'rq' extract(model, include.nobs = TRUE, include.percentile = TRUE, ...)
model |
A statistical model object. |
include.nobs |
Report the number of observations in the GOF block? |
include.percentile |
Report the percentile (tau)? |
... |
Custom parameters, which are handed over to subroutines, in this
case to the |
extract method for Sarlm objectsextract method for Sarlm objects created by the
lagsarlm function in the spatialreg
package.
## S4 method for signature 'Sarlm' extract( model, include.nobs = TRUE, include.loglik = TRUE, include.aic = TRUE, include.lr = TRUE, include.wald = TRUE, ... )## S4 method for signature 'Sarlm' extract( model, include.nobs = TRUE, include.loglik = TRUE, include.aic = TRUE, include.lr = TRUE, include.wald = TRUE, ... )
model |
A statistical model object. |
include.nobs |
Report the number of observations in the GOF block? |
include.loglik |
Report the log likelihood in the GOF block? |
include.aic |
Report Akaike's Information Criterion (AIC) in the GOF block? |
include.lr |
Report likelihood ratio test? |
include.wald |
Report the Wald statistic? |
... |
Custom parameters, which are handed over to subroutines, in this
case to the |
extract method for sclm objectsextract method for sclm objects created by the
clm function in the ordinal package.
## S4 method for signature 'sclm' extract( model, include.thresholds = TRUE, include.aic = TRUE, include.bic = TRUE, include.loglik = TRUE, include.nobs = TRUE, ... )## S4 method for signature 'sclm' extract( model, include.thresholds = TRUE, include.aic = TRUE, include.bic = TRUE, include.loglik = TRUE, include.nobs = TRUE, ... )
model |
A statistical model object. |
include.thresholds |
Report thresholds in the GOF block? |
include.aic |
Report Akaike's Information Criterion (AIC) in the GOF block? |
include.bic |
Report the Bayesian Information Criterion (BIC) in the GOF block? |
include.loglik |
Report the log likelihood in the GOF block? |
include.nobs |
Report the number of observations in the GOF block? |
... |
Custom parameters, which are handed over to subroutines, in this
case to the |
extract method for selection objectsextract method for selection objects created by the
selection function in the sampleSelection package.
## S4 method for signature 'selection' extract( model, prefix = TRUE, include.selection = TRUE, include.outcome = TRUE, include.errors = TRUE, include.aic = TRUE, include.bic = TRUE, include.loglik = TRUE, include.rsquared = TRUE, include.adjrs = TRUE, include.nobs = TRUE, ... )## S4 method for signature 'selection' extract( model, prefix = TRUE, include.selection = TRUE, include.outcome = TRUE, include.errors = TRUE, include.aic = TRUE, include.bic = TRUE, include.loglik = TRUE, include.rsquared = TRUE, include.adjrs = TRUE, include.nobs = TRUE, ... )
model |
A statistical model object. |
prefix |
Include prefix before the label of the coefficient in order to identify the current model component? |
include.selection |
Report the selection component of a sample selection model? |
include.outcome |
Report the outcome component of a sample selection model? |
include.errors |
Report the error terms of a sample selection model? |
include.aic |
Report Akaike's Information Criterion (AIC) in the GOF |
include.bic |
Report the Bayesian Information Criterion (BIC) in the GOF block? |
include.loglik |
Report the log likelihood in the GOF block? |
include.rsquared |
Report R^2 in the GOF block? |
include.adjrs |
Report adjusted R^2 in the GOF block? |
include.nobs |
Report the number of observations in the GOF block? block? |
... |
Custom parameters, which are handed over to subroutines, in this
case to the |
extract method for sienaFit objectsextract method for sienaFit objects created by the
siena07 function in the RSiena package.
## S4 method for signature 'sienaFit' extract(model, include.iterations = TRUE, ...)## S4 method for signature 'sienaFit' extract(model, include.iterations = TRUE, ...)
model |
A statistical model object. |
include.iterations |
Report the number of iterations? |
... |
Custom parameters, which are handed over to subroutines, in this
case to the |
extract method for simex objectsextract method for simex objects created by the
simex function in the simex package.
## S4 method for signature 'simex' extract(model, jackknife = TRUE, include.nobs = TRUE, ...)## S4 method for signature 'simex' extract(model, jackknife = TRUE, include.nobs = TRUE, ...)
model |
A statistical model object. |
jackknife |
Use Jackknife variance instead of asymptotic variance? |
include.nobs |
Report the number of observations in the GOF block? |
... |
Custom parameters, which are handed over to subroutines, in this
case to the |
extract method for speedglm objectsextract method for speedglm objects created by the
speedglm function in the speedglm
package.
## S4 method for signature 'speedglm' extract( model, include.aic = TRUE, include.bic = TRUE, include.loglik = TRUE, include.deviance = TRUE, include.nobs = TRUE, ... )## S4 method for signature 'speedglm' extract( model, include.aic = TRUE, include.bic = TRUE, include.loglik = TRUE, include.deviance = TRUE, include.nobs = TRUE, ... )
model |
A statistical model object. |
include.aic |
Report Akaike's Information Criterion (AIC) in the GOF block? |
include.bic |
Report the Bayesian Information Criterion (BIC) in the GOF block? |
include.loglik |
Report the log likelihood in the GOF block? |
include.deviance |
Report the deviance? |
include.nobs |
Report the number of observations in the GOF block? |
... |
Custom parameters, which are handed over to subroutines, in this
case to the |
extract method for speedlm objectsextract method for speedlm objects created by the
speedlm function in the speedglm
package.
## S4 method for signature 'speedlm' extract( model, include.rsquared = TRUE, include.adjrs = TRUE, include.nobs = TRUE, include.fstatistic = FALSE, include.rmse = FALSE, ... )## S4 method for signature 'speedlm' extract( model, include.rsquared = TRUE, include.adjrs = TRUE, include.nobs = TRUE, include.fstatistic = FALSE, include.rmse = FALSE, ... )
model |
A statistical model object. |
include.rsquared |
Report R^2 in the GOF block? |
include.adjrs |
Report adjusted R^2 in the GOF block? |
include.nobs |
Report the number of observations in the GOF block? |
include.fstatistic |
Report the F-statistic in the GOF block? |
include.rmse |
Report the root mean square error (RMSE; = residual standard deviation) in the GOF block? |
... |
Custom parameters, which are handed over to subroutines, in this
case to the |
extract method for stergm objectsextract method for stergm objects created by the
stergm function in the tergm package.
## S4 method for signature 'stergm' extract( model, beside = FALSE, include.formation = TRUE, include.dissolution = TRUE, include.nvertices = TRUE, include.aic = FALSE, include.bic = FALSE, include.loglik = FALSE, ... )## S4 method for signature 'stergm' extract( model, beside = FALSE, include.formation = TRUE, include.dissolution = TRUE, include.nvertices = TRUE, include.aic = FALSE, include.bic = FALSE, include.loglik = FALSE, ... )
model |
A statistical model object. |
beside |
Arrange the model terms below each other or beside each other?
In a |
include.formation |
Report the coefficients for the formation process in a STERGM? |
include.dissolution |
Report the coefficients for the dissolution process in a STERGM? |
include.nvertices |
Report the number of vertices in a STERGM? |
include.aic |
Report Akaike's Information Criterion (AIC) in the GOF block? |
include.bic |
Report the Bayesian Information Criterion (BIC) in the GOF block? |
include.loglik |
Report the log likelihood in the GOF block? |
... |
Custom parameters, which are handed over to subroutines, in this
case to the |
extract method for summary.lm objectsextract method for summary.lm objects created by the
summary method for lm objects, defined in the stats
package (see summary.lm).
## S4 method for signature 'summary.lm' extract( model, include.rsquared = TRUE, include.adjrs = TRUE, include.nobs = TRUE, include.fstatistic = FALSE, include.rmse = TRUE, ... )## S4 method for signature 'summary.lm' extract( model, include.rsquared = TRUE, include.adjrs = TRUE, include.nobs = TRUE, include.fstatistic = FALSE, include.rmse = TRUE, ... )
model |
A statistical model object. |
include.rsquared |
Report R^2 in the GOF block? |
include.adjrs |
Report adjusted R^2 in the GOF block? |
include.nobs |
Report the number of observations in the GOF block? |
include.fstatistic |
Report the F-statistic in the GOF block? |
include.rmse |
Report the root mean square error (RMSE; = residual standard deviation) in the GOF block? |
... |
Custom parameters, which are handed over to subroutines. Currently not in use. |
extract method for survreg objectsextract method for survreg objects created by the
survreg function in the survival package.
## S4 method for signature 'survreg' extract( model, include.aic = TRUE, include.bic = TRUE, include.loglik = TRUE, include.deviance = TRUE, include.nobs = TRUE, ... )## S4 method for signature 'survreg' extract( model, include.aic = TRUE, include.bic = TRUE, include.loglik = TRUE, include.deviance = TRUE, include.nobs = TRUE, ... )
model |
A statistical model object. |
include.aic |
Report Akaike's Information Criterion (AIC) in the GOF block? |
include.bic |
Report the Bayesian Information Criterion (BIC) in the GOF block? |
include.loglik |
Report the log likelihood in the GOF block? |
include.deviance |
Report the deviance? |
include.nobs |
Report the number of observations in the GOF block? |
... |
Custom parameters, which are handed over to subroutines, in this
case to the |
extract method for survreg.penal objectsextract method for survreg.penal objects created by the
survreg function in the survival package.
## S4 method for signature 'survreg.penal' extract( model, include.aic = TRUE, include.bic = TRUE, include.loglik = TRUE, include.deviance = TRUE, include.nobs = TRUE, ... )## S4 method for signature 'survreg.penal' extract( model, include.aic = TRUE, include.bic = TRUE, include.loglik = TRUE, include.deviance = TRUE, include.nobs = TRUE, ... )
model |
A statistical model object. |
include.aic |
Report Akaike's Information Criterion (AIC) in the GOF block? |
include.bic |
Report the Bayesian Information Criterion (BIC) in the GOF block? |
include.loglik |
Report the log likelihood in the GOF block? |
include.deviance |
Report the deviance? |
include.nobs |
Report the number of observations in the GOF block? |
... |
Custom parameters, which are handed over to subroutines, in this
case to the |
extract method for svyglm objectsextract method for svyglm objects created by the
svyglm function in the survey package.
## S4 method for signature 'svyglm' extract( model, include.aic = FALSE, include.bic = FALSE, include.loglik = FALSE, include.deviance = TRUE, include.dispersion = TRUE, include.nobs = TRUE, ... )## S4 method for signature 'svyglm' extract( model, include.aic = FALSE, include.bic = FALSE, include.loglik = FALSE, include.deviance = TRUE, include.dispersion = TRUE, include.nobs = TRUE, ... )
model |
A statistical model object. |
include.aic |
Report Akaike's Information Criterion (AIC) in the GOF block? |
include.bic |
Report the Bayesian Information Criterion (BIC) in the GOF block? |
include.loglik |
Report the log likelihood in the GOF block? |
include.deviance |
Report the deviance? |
include.dispersion |
Report the dispersion parameter? |
include.nobs |
Report the number of observations in the GOF block? |
... |
Custom parameters, which are handed over to subroutines, in this
case to the |
extract method for systemfit objectsextract method for systemfit objects created by the
systemfit function in the systemfit package.
## S4 method for signature 'systemfit' extract( model, include.rsquared = TRUE, include.adjrs = TRUE, include.nobs = TRUE, beside = FALSE, include.suffix = FALSE, ... )## S4 method for signature 'systemfit' extract( model, include.rsquared = TRUE, include.adjrs = TRUE, include.nobs = TRUE, beside = FALSE, include.suffix = FALSE, ... )
model |
A statistical model object. |
include.rsquared |
Report R^2 in the GOF block? |
include.adjrs |
Report adjusted R^2 in the GOF block? |
include.nobs |
Report the number of observations in the GOF block? |
beside |
Arrange the model terms below each other or beside each other, in separate columns? |
include.suffix |
Report the name of the current model in parentheses after each model term (instead of before the model term)? |
... |
Custom parameters, which are handed over to subroutines, in this
case to the |
extract method for texreg objectsextract method for texreg objects created by the
extract function in the texreg package.
## S4 method for signature 'texreg' extract(model, ...)## S4 method for signature 'texreg' extract(model, ...)
model |
A statistical model object. |
... |
Custom parameters, which are handed over to subroutines. Currently not in use. |
extract method for tobit objectsextract method for tobit objects created by the
tobit function in the AER package.
## S4 method for signature 'tobit' extract( model, include.aic = TRUE, include.bic = TRUE, include.loglik = TRUE, include.deviance = TRUE, include.nobs = FALSE, include.censnobs = TRUE, include.wald = TRUE, ... )## S4 method for signature 'tobit' extract( model, include.aic = TRUE, include.bic = TRUE, include.loglik = TRUE, include.deviance = TRUE, include.nobs = FALSE, include.censnobs = TRUE, include.wald = TRUE, ... )
model |
A statistical model object. |
include.aic |
Report Akaike's Information Criterion (AIC) in the GOF block? |
include.bic |
Report the Bayesian Information Criterion (BIC) in the GOF block? |
include.loglik |
Report the log likelihood in the GOF block? |
include.deviance |
Report the deviance? |
include.nobs |
Report the number of observations in the GOF block? |
include.censnobs |
Report the total, right-censored, left-censored, and uncensored number of observations? |
include.wald |
Report the Wald statistic? |
... |
Custom parameters, which are handed over to subroutines, in this
case to the |
extract method for truncreg objectsextract method for truncreg objects created by the
truncreg function in the truncreg package.
## S4 method for signature 'truncreg' extract( model, include.nobs = TRUE, include.loglik = TRUE, include.aic = TRUE, include.bic = TRUE, ... )## S4 method for signature 'truncreg' extract( model, include.nobs = TRUE, include.loglik = TRUE, include.aic = TRUE, include.bic = TRUE, ... )
model |
A statistical model object. |
include.nobs |
Report the number of observations in the GOF block? |
include.loglik |
Report the log likelihood in the GOF block? |
include.aic |
Report Akaike's Information Criterion (AIC) in the GOF block? |
include.bic |
Report the Bayesian Information Criterion (BIC) in the GOF block? |
... |
Custom parameters, which are handed over to subroutines. Currently not in use. |
extract method for vglm objectsextract method for vglm objects created by the
vglm function in the VGAM package.
## S4 method for signature 'vglm' extract( model, include.loglik = TRUE, include.df = TRUE, include.nobs = TRUE, ... )## S4 method for signature 'vglm' extract( model, include.loglik = TRUE, include.df = TRUE, include.nobs = TRUE, ... )
model |
A statistical model object. |
include.loglik |
Report the log likelihood in the GOF block? |
include.df |
Report the degrees of freedom? |
include.nobs |
Report the number of observations in the GOF block? |
... |
Custom parameters, which are handed over to subroutines. Currently not in use. |
Christoph Riedl <[email protected]>
extract method for weibreg objectsextract method for weibreg objects created by the
weibreg function in the eha package.
## S4 method for signature 'weibreg' extract( model, include.aic = TRUE, include.loglik = TRUE, include.lr = TRUE, include.nobs = TRUE, include.events = TRUE, include.trisk = TRUE, ... )## S4 method for signature 'weibreg' extract( model, include.aic = TRUE, include.loglik = TRUE, include.lr = TRUE, include.nobs = TRUE, include.events = TRUE, include.trisk = TRUE, ... )
model |
A statistical model object. |
include.aic |
Report Akaike's Information Criterion (AIC) in the GOF block? |
include.loglik |
Report the log likelihood in the GOF block? |
include.lr |
Report likelihood ratio test? |
include.nobs |
Report the number of observations in the GOF block? |
include.events |
Report the number of events in the GOF block? |
include.trisk |
Report the total time at risk (in event-history models)? |
... |
Custom parameters, which are handed over to subroutines. Currently not in use. |
extract method for wls objectsextract method for wls objects created by the
wls function in the metaSEM package.
## S4 method for signature 'wls' extract( model, include.statistics = TRUE, include.nobs = TRUE, include.aic = TRUE, include.bic = TRUE, ... )## S4 method for signature 'wls' extract( model, include.statistics = TRUE, include.nobs = TRUE, include.aic = TRUE, include.bic = TRUE, ... )
model |
A statistical model object. |
include.statistics |
Report RMSEA and other GOF statistics? |
include.nobs |
Report the number of observations in the GOF block? |
include.aic |
Report AIC? |
include.bic |
Report BIC? |
... |
Custom parameters, which are handed over to subroutines. Currently not in use. |
Christoph Riedl <[email protected]>
Philip Leifeld
extract method for zeroinfl objectsextract method for zeroinfl objects created by the
zeroinfl function in the pscl package.
## S4 method for signature 'zeroinfl' extract( model, beside = FALSE, include.count = TRUE, include.zero = TRUE, include.aic = TRUE, include.loglik = TRUE, include.nobs = TRUE, ... )## S4 method for signature 'zeroinfl' extract( model, beside = FALSE, include.count = TRUE, include.zero = TRUE, include.aic = TRUE, include.loglik = TRUE, include.nobs = TRUE, ... )
model |
A statistical model object. |
beside |
Arrange the model terms below each other or beside each other? The binary model parameters and the count parameters can be displayed in two separate columns of the table. |
include.count |
Report the count parameters in the coefficients block (before the binary part for the zeros)? |
include.zero |
Should the binary part of the model be included in the coefficients block (after the count parameters)? |
include.aic |
Report Akaike's Information Criterion (AIC) in the GOF block? |
include.loglik |
Report the log likelihood in the GOF block? |
include.nobs |
Report the number of observations in the GOF block? |
... |
Custom parameters, which are handed over to subroutines, in this
case to the |
Conversion of R regression output to a HTML table.
htmlreg( l, file = NULL, single.row = FALSE, stars = c(0.001, 0.01, 0.05), custom.header = NULL, custom.model.names = NULL, custom.coef.names = NULL, custom.coef.map = NULL, custom.gof.names = NULL, custom.gof.rows = NULL, custom.note = NULL, digits = 2, leading.zero = TRUE, star.symbol = "*", symbol = "·", override.coef = 0, override.se = 0, override.pvalues = 0, override.ci.low = 0, override.ci.up = 0, omit.coef = NULL, reorder.coef = NULL, reorder.gof = NULL, ci.force = FALSE, ci.force.level = 0.95, ci.test = 0, groups = NULL, custom.columns = NULL, custom.col.pos = NULL, bold = 0, center = TRUE, caption = "Statistical models", caption.above = FALSE, inline.css = TRUE, doctype = FALSE, html.tag = FALSE, head.tag = FALSE, body.tag = FALSE, indentation = "", margin = 10, padding = 5, color = "#000000", outer.rules = 2, inner.rules = 1, ... )htmlreg( l, file = NULL, single.row = FALSE, stars = c(0.001, 0.01, 0.05), custom.header = NULL, custom.model.names = NULL, custom.coef.names = NULL, custom.coef.map = NULL, custom.gof.names = NULL, custom.gof.rows = NULL, custom.note = NULL, digits = 2, leading.zero = TRUE, star.symbol = "*", symbol = "·", override.coef = 0, override.se = 0, override.pvalues = 0, override.ci.low = 0, override.ci.up = 0, omit.coef = NULL, reorder.coef = NULL, reorder.gof = NULL, ci.force = FALSE, ci.force.level = 0.95, ci.test = 0, groups = NULL, custom.columns = NULL, custom.col.pos = NULL, bold = 0, center = TRUE, caption = "Statistical models", caption.above = FALSE, inline.css = TRUE, doctype = FALSE, html.tag = FALSE, head.tag = FALSE, body.tag = FALSE, indentation = "", margin = 10, padding = 5, color = "#000000", outer.rules = 2, inner.rules = 1, ... )
l |
A statistical model or a list of statistical models. Lists of
models can be specified as |
file |
Using this argument, the resulting table is written to a file
rather than to the R prompt. The file name can be specified as a character
string. Writing a table to a file can be useful for working with MS Office
or LibreOffice. For example, using the |
single.row |
By default, a model parameter takes up two lines of the
table: the standard error is listed in parentheses under the coefficient.
This saves a lot of horizontal space on the page and is the default table
format in most academic journals. If |
stars |
The significance levels to be used to draw stars. Between 0 and
4 threshold values can be provided as a numeric vector. For example,
|
custom.header |
An optional named list of multi-column headers that are
placed above the model names. For example,
|
custom.model.names |
A character vector of labels for the models. By
default, the models are named "Model 1", "Model 2", etc. Specifying
|
custom.coef.names |
By default, texreg uses the coefficient names
which are stored in the models. The Sometimes it happens that the same variable has a different name in different models. In this case, the user can use this function to assign identical names. If possible, the rows will then be merged into a single row unless both rows contain values in the same column. Where the argument contains an See also |
custom.coef.map |
The Users must supply a named list of this form:
|
custom.gof.names |
A character vector which is used to replace the
names of the goodness-of-fit statistics at the bottom of the table. The
vector must have the same length as the number of GOF statistics in the
final table. The argument works like the |
custom.gof.rows |
A named list of vectors for new lines at the
beginning of the GOF block of the table. For example, |
custom.note |
With this argument, a replacement text for the
significance note below the table can be provided. If an empty
If the |
digits |
Set the number of decimal places for coefficients, standard
errors and goodness-of-fit statistics. Do not use negative values! The
argument works like the |
leading.zero |
Most journals require leading zeros of coefficients and
standard errors (for example, |
star.symbol |
Alternative characters for the significance stars can be
specified. This is useful if knitr and Markdown are used for HTML
report generation. In Markdown, asterisks or stars are interpreted as
special characters, so they have to be escaped. To make a HTML table
compatible with Markdown, specify |
symbol |
If four threshold values are handed over to the |
override.coef |
Set custom values for the coefficients. New coefficients
are provided as a list of numeric vectors. The list contains vectors of
coefficients for each model. There must be as many vectors of coefficients
as there are models. For example, if there are two models with three model
terms each, the argument could be specified as |
override.se |
Set custom values for the standard errors. New standard
errors are provided as a list of numeric vectors. The list contains vectors
of standard errors for each model. There must be as many vectors of
standard errors as there are models. For example, if there are two models
with three coefficients each, the argument could be specified as
|
override.pvalues |
Set custom values for the p-values. New p-values are
provided as a list of numeric vectors. The list contains vectors of
p-values for each model. There must be as many vectors of p-values as there
are models. For example, if there are two models with three coefficients
each, the argument could be specified as |
override.ci.low |
Set custom lower confidence interval bounds. This
works like the other override arguments, with one exception: if confidence
intervals are provided here and in the |
override.ci.up |
Set custom upper confidence interval bounds. This
works like the other override arguments, with one exception: if confidence
intervals are provided here and in the |
omit.coef |
A character string which is used as a regular expression to
remove coefficient rows from the table. For example, |
reorder.coef |
Reorder the rows of the coefficient block of the
resulting table in a custom way. The argument takes a vector of the same
length as the number of coefficients. For example, if there are three
coefficients, |
reorder.gof |
Reorder the rows of the goodness-of-fit block of the
resulting table in a custom way. The argument takes a vector of the same
length as the number of GOF statistics. For example, if there are three
goodness-of-fit rows, |
ci.force |
Should confidence intervals be used instead of the default
standard errors and p-values? Most models implemented in the texreg
package report standard errors and p-values by default while few models
report confidence intervals. However, the functions in the texreg
package can convert standard errors and into confidence intervals using
z-scores if desired. To enforce confidence intervals instead of standard
errors, the |
ci.force.level |
If the |
ci.test |
If confidence intervals are reported, the |
groups |
This argument can be used to group the rows of the table into
blocks. For example, there could be one block for hypotheses and another
block for control variables. Each group has a heading, and the row labels
within a group are indented. The partitions must be handed over as a list
of named numeric vectors, where each number is a row index and each name is
the heading of the group. Example: |
custom.columns |
An optional list of additional text columns to be
inserted into the coefficient block of the table, for example coefficient
types. The list should contain one or more character vectors with as many
character or numeric elements as there are coefficients/model terms. If the
vectors in the list are named, the names are used as labels in the table
header. For example,
|
custom.col.pos |
An optional integer vector of positions for the columns
given in the |
bold |
The p-value threshold below which the coefficient shall be
formatted in a bold font. For example, |
center |
Should the table be horizontally aligned at the center of the page? |
caption |
Set the caption of the table. |
caption.above |
Should the caption of the table be placed above the table? By default, it is placed below the table. |
inline.css |
Should the CSS stylesheets be embedded directly in the code
of the table ( |
doctype |
Should the first line of the HTML code contain the DOCTYPE
definition? If |
html.tag |
Should the table code (and possibly the <body> and <head> tags) be enclosed in an <html> tag? Suppressing this tag is recommended when knitr is used for dynamic HTML or Markdown report generation. Including this tag is recommended when the code is saved to a file, for example as an MS Word document. |
head.tag |
Should the <head> tag (including CSS definitions and title/caption) be included in the HTML code? Suppressing this tag is recommended when knitr is used for dynamic HTML or Markdown report generation. Including this tag is recommended when the code is saved to a file, for example as an MS Word document. |
body.tag |
Should the table code be enclosed in a <body> HTML tag? Suppressing this tag is recommended when knitr is used for dynamic HTML or Markdown report generation. Including this tag is recommended when the code is saved to a file, for example as an MS Word document. |
indentation |
Characters used for indentation of the HTML code. By
default, |
margin |
The margin around the table in pixels. This determines how much
space there is around the table. To remove all space around the table, set
|
padding |
The space on the left and right of each table cell in pixels. |
color |
The color of the table, including text and rules or lines. This
can be provided as a hex RGB value or as a color string that is valid in
HTML (e.g., |
outer.rules |
The line width at the top and bottom of the table in
pixels. Can be |
inner.rules |
The horizontal line width before and after the coefficient
block of the table in pixels. Can be |
... |
Custom options to be passed on to the |
The htmlreg function creates HTML code. Tables in HTML format can
be saved with a ".html" extension and displayed in a web browser.
Alternatively, they can be saved with a ".doc" extension and opened in MS
Word for inclusion in office documents. htmlreg also works with
knitr and HTML or Markdown. Note that the inline.css,
doctype, html.tag, head.tag, body.tag, and
star.symbol arguments must be adjusted for the different purposes (see
the description of the arguments).
Philip Leifeld
Leifeld, Philip (2013). texreg: Conversion of Statistical Model Output in R to LaTeX and HTML Tables. Journal of Statistical Software 55(8): 1-24. doi:10.18637/jss.v055.i08.
Other texreg:
huxtablereg(),
knitreg(),
matrixreg(),
plotreg(),
screenreg(),
texreg,
wordreg()
library("nlme") model.1 <- lme(distance ~ age, data = Orthodont, random = ~ 1) model.2 <- lme(distance ~ age + Sex, data = Orthodont, random = ~ 1) htmlreg(list(model.1, model.2), file = "texreg.doc", inline.css = FALSE, doctype = TRUE, html.tag = TRUE, head.tag = TRUE, body.tag = TRUE) unlink("texreg.doc")library("nlme") model.1 <- lme(distance ~ age, data = Orthodont, random = ~ 1) model.2 <- lme(distance ~ age + Sex, data = Orthodont, random = ~ 1) htmlreg(list(model.1, model.2), file = "texreg.doc", inline.css = FALSE, doctype = TRUE, html.tag = TRUE, head.tag = TRUE, body.tag = TRUE) unlink("texreg.doc")
Create a huxtable object from multiple statistical models.
huxtablereg( l, single.row = FALSE, stars = c(0.001, 0.01, 0.05), custom.model.names = NULL, custom.coef.names = NULL, custom.coef.map = NULL, custom.gof.names = NULL, custom.gof.rows = NULL, digits = 2, leading.zero = TRUE, star.symbol = "*", symbol = "+", override.coef = 0, override.se = 0, override.pvalues = 0, override.ci.low = 0, override.ci.up = 0, omit.coef = NULL, reorder.coef = NULL, reorder.gof = NULL, ci.force = FALSE, ci.force.level = 0.95, ci.test = 0, groups = NULL, custom.columns = NULL, custom.col.pos = NULL, ... )huxtablereg( l, single.row = FALSE, stars = c(0.001, 0.01, 0.05), custom.model.names = NULL, custom.coef.names = NULL, custom.coef.map = NULL, custom.gof.names = NULL, custom.gof.rows = NULL, digits = 2, leading.zero = TRUE, star.symbol = "*", symbol = "+", override.coef = 0, override.se = 0, override.pvalues = 0, override.ci.low = 0, override.ci.up = 0, omit.coef = NULL, reorder.coef = NULL, reorder.gof = NULL, ci.force = FALSE, ci.force.level = 0.95, ci.test = 0, groups = NULL, custom.columns = NULL, custom.col.pos = NULL, ... )
l |
A statistical model or a list of statistical models. Lists of
models can be specified as |
single.row |
By default, a model parameter takes up two lines of the
table: the standard error is listed in parentheses under the coefficient.
This saves a lot of horizontal space on the page and is the default table
format in most academic journals. If |
stars |
The significance levels to be used to draw stars. Between 0 and
4 threshold values can be provided as a numeric vector. For example,
|
custom.model.names |
A character vector of labels for the models. By
default, the models are named "Model 1", "Model 2", etc. Specifying
|
custom.coef.names |
By default, texreg uses the coefficient names
which are stored in the models. The Sometimes it happens that the same variable has a different name in different models. In this case, the user can use this function to assign identical names. If possible, the rows will then be merged into a single row unless both rows contain values in the same column. Where the argument contains an See also |
custom.coef.map |
The Users must supply a named list of this form:
|
custom.gof.names |
A character vector which is used to replace the
names of the goodness-of-fit statistics at the bottom of the table. The
vector must have the same length as the number of GOF statistics in the
final table. The argument works like the |
custom.gof.rows |
A named list of vectors for new lines at the
beginning of the GOF block of the table. For example, |
digits |
Set the number of decimal places for coefficients, standard
errors and goodness-of-fit statistics. Do not use negative values! The
argument works like the |
leading.zero |
Most journals require leading zeros of coefficients and
standard errors (for example, |
star.symbol |
Alternative characters for the significance stars can be
specified. This is useful if knitr and Markdown are used for HTML
report generation. In Markdown, asterisks or stars are interpreted as
special characters, so they have to be escaped. To make a HTML table
compatible with Markdown, specify |
symbol |
If four threshold values are handed over to the |
override.coef |
Set custom values for the coefficients. New coefficients
are provided as a list of numeric vectors. The list contains vectors of
coefficients for each model. There must be as many vectors of coefficients
as there are models. For example, if there are two models with three model
terms each, the argument could be specified as |
override.se |
Set custom values for the standard errors. New standard
errors are provided as a list of numeric vectors. The list contains vectors
of standard errors for each model. There must be as many vectors of
standard errors as there are models. For example, if there are two models
with three coefficients each, the argument could be specified as
|
override.pvalues |
Set custom values for the p-values. New p-values are
provided as a list of numeric vectors. The list contains vectors of
p-values for each model. There must be as many vectors of p-values as there
are models. For example, if there are two models with three coefficients
each, the argument could be specified as |
override.ci.low |
Set custom lower confidence interval bounds. This
works like the other override arguments, with one exception: if confidence
intervals are provided here and in the |
override.ci.up |
Set custom upper confidence interval bounds. This
works like the other override arguments, with one exception: if confidence
intervals are provided here and in the |
omit.coef |
A character string which is used as a regular expression to
remove coefficient rows from the table. For example, |
reorder.coef |
Reorder the rows of the coefficient block of the
resulting table in a custom way. The argument takes a vector of the same
length as the number of coefficients. For example, if there are three
coefficients, |
reorder.gof |
Reorder the rows of the goodness-of-fit block of the
resulting table in a custom way. The argument takes a vector of the same
length as the number of GOF statistics. For example, if there are three
goodness-of-fit rows, |
ci.force |
Should confidence intervals be used instead of the default
standard errors and p-values? Most models implemented in the texreg
package report standard errors and p-values by default while few models
report confidence intervals. However, the functions in the texreg
package can convert standard errors and into confidence intervals using
z-scores if desired. To enforce confidence intervals instead of standard
errors, the |
ci.force.level |
If the |
ci.test |
If confidence intervals are reported, the |
groups |
This argument can be used to group the rows of the table into
blocks. For example, there could be one block for hypotheses and another
block for control variables. Each group has a heading, and the row labels
within a group are indented. The partitions must be handed over as a list
of named numeric vectors, where each number is a row index and each name is
the heading of the group. Example: |
custom.columns |
An optional list of additional text columns to be
inserted into the coefficient block of the table, for example coefficient
types. The list should contain one or more character vectors with as many
character or numeric elements as there are coefficients/model terms. If the
vectors in the list are named, the names are used as labels in the table
header. For example,
|
custom.col.pos |
An optional integer vector of positions for the columns
given in the |
... |
Custom options to be passed on to the |
The huxtablereg function creates a
huxtable object using the huxtable package.
This allows output to HTML, LaTeX, Word, Excel, Powerpoint, and RTF. The
object can be formatted using huxtable package functions. See also
huxreg.
David Hugh-Jones
Other texreg:
htmlreg(),
knitreg(),
matrixreg(),
plotreg(),
screenreg(),
texreg,
wordreg()
library("nlme") model.1 <- lme(distance ~ age, data = Orthodont, random = ~ 1) model.2 <- lme(distance ~ age + Sex, data = Orthodont, random = ~ 1) if (requireNamespace("huxtable")) { hr <- huxtablereg(list(model.1, model.2)) hr <- huxtable::set_bottom_border(hr, 1, -1, 0.4) hr <- huxtable::set_bold(hr, 1:nrow(hr), 1, TRUE) hr <- huxtable::set_bold(hr, 1, -1, TRUE) hr <- huxtable::set_all_borders(hr, 4, 2, 0.4) hr <- huxtable::set_all_border_colors(hr, 4, 2, "red") hr ## Not run: huxtable::quick_pdf(hr) huxtable::quick_docx(hr) # or use in a knitr document ## End(Not run) }library("nlme") model.1 <- lme(distance ~ age, data = Orthodont, random = ~ 1) model.2 <- lme(distance ~ age + Sex, data = Orthodont, random = ~ 1) if (requireNamespace("huxtable")) { hr <- huxtablereg(list(model.1, model.2)) hr <- huxtable::set_bottom_border(hr, 1, -1, 0.4) hr <- huxtable::set_bold(hr, 1:nrow(hr), 1, TRUE) hr <- huxtable::set_bold(hr, 1, -1, TRUE) hr <- huxtable::set_all_borders(hr, 4, 2, 0.4) hr <- huxtable::set_all_border_colors(hr, 4, 2, "red") hr ## Not run: huxtable::quick_pdf(hr) huxtable::quick_docx(hr) # or use in a knitr document ## End(Not run) }
Flexibly choose the right table output format for use with knitr.
knitreg(...)knitreg(...)
... |
Arguments to be handed over to the texreg, htmlreg, screenreg, or matrixreg function. See the respective help page for details. |
This function automatically selects the right function (texreg, screenreg, htmlreg, or matrixreg) with the right set of arguments for use with the knitr package, for example in RStudio. The advantage of using this function with knitr is that the user does not need to replace the texreg, htmlreg etc. function call in the document when a different output format is selected.
knitreg works with...
R HTML documents (.Rhtml extension)
R Sweave documents (.Rnw extension) for PDF output via LaTeX,
rendered using...
the knitr package
the Sweave package
R Markdown documents (.Rmd extension), rendered as...
HTML documents
PDF documents
Word documents
Powerpoint presentations
Presentations (.Rpres extension, not .Rmd)
R Notebooks, including preview
If Markdown and HTML rendering are selected, htmlreg arguments
doctype = FALSE and star.symbol = "*" are set to enable
compatibility with Markdown. With R HTML documents (but not Markdown) or
presentations (.Rpres extension), only doctype = FALSE is set.
For PDF/LaTeX documents, the texreg argument
use.packages = FALSE is set to suppress any package loading
instructions in the preamble. The user must load any packages manually in the
preamble of the document.
The knitr and rmarkdown packages must be installed for this function to work.
A table as a character string in the respective output format.
Philip Leifeld, with input from David Hugh-Jones
Other texreg:
htmlreg(),
huxtablereg(),
matrixreg(),
plotreg(),
screenreg(),
texreg,
wordreg()
require("nlme") model.1 <- lme(distance ~ age, data = Orthodont, random = ~ 1) model.2 <- lme(distance ~ age + Sex, data = Orthodont, random = ~ 1) knitreg(list(model.1, model.2), center = FALSE, caption = "", table = FALSE)require("nlme") model.1 <- lme(distance ~ age, data = Orthodont, random = ~ 1) model.2 <- lme(distance ~ age + Sex, data = Orthodont, random = ~ 1) knitreg(list(model.1, model.2), center = FALSE, caption = "", table = FALSE)
character matrixConversion of R regression output to a character matrix.
matrixreg( l, single.row = FALSE, stars = c(0.001, 0.01, 0.05), custom.model.names = NULL, custom.coef.names = NULL, custom.coef.map = NULL, custom.gof.names = NULL, custom.gof.rows = NULL, digits = 2, leading.zero = TRUE, star.symbol = "*", symbol = ".", override.coef = 0, override.se = 0, override.pvalues = 0, override.ci.low = 0, override.ci.up = 0, omit.coef = NULL, reorder.coef = NULL, reorder.gof = NULL, ci.force = FALSE, ci.force.level = 0.95, ci.test = 0, bold = 0, groups = NULL, custom.columns = NULL, custom.col.pos = NULL, dcolumn = TRUE, siunitx = FALSE, output.type = c("ascii", "latex", "html"), include.attributes = FALSE, trim = FALSE, ... )matrixreg( l, single.row = FALSE, stars = c(0.001, 0.01, 0.05), custom.model.names = NULL, custom.coef.names = NULL, custom.coef.map = NULL, custom.gof.names = NULL, custom.gof.rows = NULL, digits = 2, leading.zero = TRUE, star.symbol = "*", symbol = ".", override.coef = 0, override.se = 0, override.pvalues = 0, override.ci.low = 0, override.ci.up = 0, omit.coef = NULL, reorder.coef = NULL, reorder.gof = NULL, ci.force = FALSE, ci.force.level = 0.95, ci.test = 0, bold = 0, groups = NULL, custom.columns = NULL, custom.col.pos = NULL, dcolumn = TRUE, siunitx = FALSE, output.type = c("ascii", "latex", "html"), include.attributes = FALSE, trim = FALSE, ... )
l |
A statistical model or a list of statistical models. Lists of
models can be specified as |
single.row |
By default, a model parameter takes up two lines of the
table: the standard error is listed in parentheses under the coefficient.
This saves a lot of horizontal space on the page and is the default table
format in most academic journals. If |
stars |
The significance levels to be used to draw stars. Between 0 and
4 threshold values can be provided as a numeric vector. For example,
|
custom.model.names |
A character vector of labels for the models. By
default, the models are named "Model 1", "Model 2", etc. Specifying
|
custom.coef.names |
By default, texreg uses the coefficient names
which are stored in the models. The Sometimes it happens that the same variable has a different name in different models. In this case, the user can use this function to assign identical names. If possible, the rows will then be merged into a single row unless both rows contain values in the same column. Where the argument contains an See also |
custom.coef.map |
The Users must supply a named list of this form:
|
custom.gof.names |
A character vector which is used to replace the
names of the goodness-of-fit statistics at the bottom of the table. The
vector must have the same length as the number of GOF statistics in the
final table. The argument works like the |
custom.gof.rows |
A named list of vectors for new lines at the
beginning of the GOF block of the table. For example, |
digits |
Set the number of decimal places for coefficients, standard
errors and goodness-of-fit statistics. Do not use negative values! The
argument works like the |
leading.zero |
Most journals require leading zeros of coefficients and
standard errors (for example, |
star.symbol |
Alternative characters for the significance stars can be
specified. This is useful if knitr and Markdown are used for HTML
report generation. In Markdown, asterisks or stars are interpreted as
special characters, so they have to be escaped. To make a HTML table
compatible with Markdown, specify |
symbol |
If four threshold values are handed over to the |
override.coef |
Set custom values for the coefficients. New coefficients
are provided as a list of numeric vectors. The list contains vectors of
coefficients for each model. There must be as many vectors of coefficients
as there are models. For example, if there are two models with three model
terms each, the argument could be specified as |
override.se |
Set custom values for the standard errors. New standard
errors are provided as a list of numeric vectors. The list contains vectors
of standard errors for each model. There must be as many vectors of
standard errors as there are models. For example, if there are two models
with three coefficients each, the argument could be specified as
|
override.pvalues |
Set custom values for the p-values. New p-values are
provided as a list of numeric vectors. The list contains vectors of
p-values for each model. There must be as many vectors of p-values as there
are models. For example, if there are two models with three coefficients
each, the argument could be specified as |
override.ci.low |
Set custom lower confidence interval bounds. This
works like the other override arguments, with one exception: if confidence
intervals are provided here and in the |
override.ci.up |
Set custom upper confidence interval bounds. This
works like the other override arguments, with one exception: if confidence
intervals are provided here and in the |
omit.coef |
A character string which is used as a regular expression to
remove coefficient rows from the table. For example, |
reorder.coef |
Reorder the rows of the coefficient block of the
resulting table in a custom way. The argument takes a vector of the same
length as the number of coefficients. For example, if there are three
coefficients, |
reorder.gof |
Reorder the rows of the goodness-of-fit block of the
resulting table in a custom way. The argument takes a vector of the same
length as the number of GOF statistics. For example, if there are three
goodness-of-fit rows, |
ci.force |
Should confidence intervals be used instead of the default
standard errors and p-values? Most models implemented in the texreg
package report standard errors and p-values by default while few models
report confidence intervals. However, the functions in the texreg
package can convert standard errors and into confidence intervals using
z-scores if desired. To enforce confidence intervals instead of standard
errors, the |
ci.force.level |
If the |
ci.test |
If confidence intervals are reported, the |
bold |
The p-value threshold below which the coefficient shall be
formatted in a bold font. For example, |
groups |
This argument can be used to group the rows of the table into
blocks. For example, there could be one block for hypotheses and another
block for control variables. Each group has a heading, and the row labels
within a group are indented. The partitions must be handed over as a list
of named numeric vectors, where each number is a row index and each name is
the heading of the group. Example: |
custom.columns |
An optional list of additional text columns to be
inserted into the coefficient block of the table, for example coefficient
types. The list should contain one or more character vectors with as many
character or numeric elements as there are coefficients/model terms. If the
vectors in the list are named, the names are used as labels in the table
header. For example,
|
custom.col.pos |
An optional integer vector of positions for the columns
given in the |
dcolumn |
Use the dcolumn LaTeX package to get a nice alignment of
the coefficients at the decimal separator (recommended for use with the
|
siunitx |
Use the siunitx LaTeX package to get a nice alignment of
the coefficients at the decimal separator (recommended for use with the
|
output.type |
Which type of output should be produced? Valid values are
|
include.attributes |
Add some attributes to the return object for
confidence intervals, coefficient names, GOF statistic names, and model
names? These are used by |
trim |
Trim leading and trailing white space in the table cells? If
|
... |
Custom options to be passed on to the |
The matrixreg function creates a character matrix with the row
names for the coefficients and goodness-of-fit statistics in the first
column. The function is used under the hood by other functions like
screenreg or texreg but can also be called
directly.
A character matrix with the coefficients and goodness-of-fit
statistics and their column names.
Philip Leifeld
Other texreg:
htmlreg(),
huxtablereg(),
knitreg(),
plotreg(),
screenreg(),
texreg,
wordreg()
Create coefficient plots of R regression output using ggplot2.
plotreg( l, file = NULL, custom.model.names = NULL, custom.title = NULL, custom.coef.names = NULL, custom.coef.map = NULL, custom.note = NULL, override.coef = 0, override.se = 0, override.pval = 0, override.ci.low = 0, override.ci.up = 0, override.pvalues = 0, omit.coef = NULL, reorder.coef = NULL, ci.level = 0.95, ci.force = FALSE, ci.force.level = 0.95, ci.test = 0, type = "facet", theme = NULL, signif.light = "#FBC9B9", signif.medium = "#F7523A", signif.dark = "#BD0017", insignif.light = "#C5DBE9", insignif.medium = "#5A9ECC", insignif.dark = "#1C5BA6", ... )plotreg( l, file = NULL, custom.model.names = NULL, custom.title = NULL, custom.coef.names = NULL, custom.coef.map = NULL, custom.note = NULL, override.coef = 0, override.se = 0, override.pval = 0, override.ci.low = 0, override.ci.up = 0, override.pvalues = 0, omit.coef = NULL, reorder.coef = NULL, ci.level = 0.95, ci.force = FALSE, ci.force.level = 0.95, ci.test = 0, type = "facet", theme = NULL, signif.light = "#FBC9B9", signif.medium = "#F7523A", signif.dark = "#BD0017", insignif.light = "#C5DBE9", insignif.medium = "#5A9ECC", insignif.dark = "#1C5BA6", ... )
l |
A statistical model or a list of statistical models. Lists of
models can be specified as |
file |
Using this argument, the resulting table is written to a file
rather than to the R prompt. The file name can be specified as a character
string. Writing a table to a file can be useful for working with MS Office
or LibreOffice. For example, using the |
custom.model.names |
A character vector of labels for the models. By
default, the models are named "Model 1", "Model 2", etc. Specifying
|
custom.title |
With this argument, a replacement text for the
|
custom.coef.names |
By default, texreg uses the coefficient names
which are stored in the models. The Sometimes it happens that the same variable has a different name in different models. In this case, the user can use this function to assign identical names. If possible, the rows will then be merged into a single row unless both rows contain values in the same column. Where the argument contains an See also |
custom.coef.map |
The Users must supply a named list of this form:
|
custom.note |
With this argument, a replacement text for the
significance note below the table can be provided. If an empty
If the |
override.coef |
Set custom values for the coefficients. New coefficients
are provided as a list of numeric vectors. The list contains vectors of
coefficients for each model. There must be as many vectors of coefficients
as there are models. For example, if there are two models with three model
terms each, the argument could be specified as |
override.se |
Set custom values for the standard errors. New standard
errors are provided as a list of numeric vectors. The list contains vectors
of standard errors for each model. There must be as many vectors of
standard errors as there are models. For example, if there are two models
with three coefficients each, the argument could be specified as
|
override.pval |
Set custom values for the p-values. New p-values are
provided as a list of numeric vectors. The list contains vectors of
p-values for each model. There must be as many vectors of p-values as there
are models. For example, if there are two models with three coefficients
each, the argument could be specified as |
override.ci.low |
Set custom lower confidence interval bounds. This
works like the other override arguments, with one exception: if confidence
intervals are provided here and in the |
override.ci.up |
Set custom upper confidence interval bounds. This
works like the other override arguments, with one exception: if confidence
intervals are provided here and in the |
override.pvalues |
Set custom values for the p-values. New p-values are
provided as a list of numeric vectors. The list contains vectors of
p-values for each model. There must be as many vectors of p-values as there
are models. For example, if there are two models with three coefficients
each, the argument could be specified as |
omit.coef |
A character string which is used as a regular expression to
remove coefficient rows from the table. For example, |
reorder.coef |
Reorder the rows of the coefficient block of the
resulting table in a custom way. The argument takes a vector of the same
length as the number of coefficients. For example, if there are three
coefficients, |
ci.level |
If standard errors are converted to confidence intervals
(because a model does not natively support CIs), what confidence level
should be used for the outer confidence interval? By default, |
ci.force |
Should confidence intervals be used instead of the default
standard errors and p-values? Most models implemented in the texreg
package report standard errors and p-values by default while few models
report confidence intervals. However, the functions in the texreg
package can convert standard errors and into confidence intervals using
z-scores if desired. To enforce confidence intervals instead of standard
errors, the |
ci.force.level |
If the |
ci.test |
If confidence intervals are reported, the |
type |
The default option is |
theme |
The |
signif.light |
Color of outer confidence intervals for significant model terms. |
signif.medium |
Color of inner confidence intervals for significant model terms. |
signif.dark |
Color of point estimates and labels for significant model terms. |
insignif.light |
Color of outer confidence intervals for insignificant model terms. |
insignif.medium |
Color of inner confidence intervals for insignificant model terms. |
insignif.dark |
Color of point estimates and labels for insignificant model terms. |
... |
Custom options to be passed on to the |
The plotreg function produces coefficient plots (i.e., forest plots
applied to point estimates and confidence intervals) and works much like the
screenreg, texreg, htmlreg,
matrixreg and wordreg functions. It accepts a
single model or multiple statistical models as input and internally extracts
the relevant data from the models. If confidence intervals are not defined in
the extract method of a statistical model (see extract), the default
standard errors are converted to confidence intervals. Most of the arguments
work like in the screenreg, texreg, and
htmlreg matrixreg, and wordreg
functions. It is possible to display the plots in two ways: using the
type = "facet" argument, one forest plot applied to point estimates
and confidence intervals will be visualized in case there is only one model.
If there is more than one model, each one will be plotted next to the other
as a separate facet; using the type = "forest" argument, coefficients
from one or more models will be grouped together and displayed as a single
forest plot.
Coefficient plot as a ggplot2 gg object if
file = FALSE. NULL otherwise.
Claudia Zucca, Philip Leifeld
texreg-package extract
texreg matrixreg
Other texreg:
htmlreg(),
huxtablereg(),
knitreg(),
matrixreg(),
screenreg(),
texreg,
wordreg()
## Not run: # example from the 'lm' help file: ctl <- c(4.17, 5.58, 5.18, 6.11, 4.50, 4.61, 5.17, 4.53, 5.33, 5.14) trt <- c(4.81, 4.17, 4.41, 3.59, 5.87, 3.83, 6.03, 4.89, 4.32, 4.69) group <- gl(2, 10, 20, labels = c("Ctl", "Trt")) weight <- c(ctl, trt) lm.D9 <- lm(weight ~ group) lm.D90 <- lm(weight ~ group - 1) plotreg(lm.D9) # plot model output as a diagram # customize theme and title and save as a PDF file. plotreg(lm.D9, theme = theme_dark(), ggtitle = "my title", file = "myplot.pdf") unlink("myplot.pdf") # group coefficients from multiple models plotreg(list(lm.D9, lm.D90), type = "forest") ## End(Not run)## Not run: # example from the 'lm' help file: ctl <- c(4.17, 5.58, 5.18, 6.11, 4.50, 4.61, 5.17, 4.53, 5.33, 5.14) trt <- c(4.81, 4.17, 4.41, 3.59, 5.87, 3.83, 6.03, 4.89, 4.32, 4.69) group <- gl(2, 10, 20, labels = c("Ctl", "Trt")) weight <- c(ctl, trt) lm.D9 <- lm(weight ~ group) lm.D90 <- lm(weight ~ group - 1) plotreg(lm.D9) # plot model output as a diagram # customize theme and title and save as a PDF file. plotreg(lm.D9, theme = theme_dark(), ggtitle = "my title", file = "myplot.pdf") unlink("myplot.pdf") # group coefficients from multiple models plotreg(list(lm.D9, lm.D90), type = "forest") ## End(Not run)
Publish praise about texreg to help the developers demonstrate impact.
praise( academic_user, organization, name = NULL, general_praise = NULL, increase_productivity = NULL, increase_quality = NULL, start_using = NULL, where_learn = NULL, contact_details = NULL, models = NULL, num_users = NULL, return.response = FALSE ) praise_interactive()praise( academic_user, organization, name = NULL, general_praise = NULL, increase_productivity = NULL, increase_quality = NULL, start_using = NULL, where_learn = NULL, contact_details = NULL, models = NULL, num_users = NULL, return.response = FALSE ) praise_interactive()
academic_user |
Should be |
organization |
Please tell us the name of the organization for which you are using texreg. If we can show that the package is being employed in a number of different settings, this will help us demonstrate impact. |
name |
(Optional) We would be delighted to to know who you are. After all, we can quote you much more effectively if we can tell the funders and employers who provided this praise! If possible, include your title. |
general_praise |
Use this argument to provide general praise, for
example about the way it was designed, the user support you have received,
or just how much you enjoy using it. While this is useful, however, we
would be even more interested in receiving statements in how texreg
makes you more productive (in the |
increase_productivity |
This is one of the fields we are most interested
in. Please use this field to tell us how texreg is making you more
productive. For example, does it speed up writing your articles or research
reports? Does it enable you to skip manual work like copy and paste of your
results into your reports, or to avoid fiddling with table formatting? How
much time has it saved you so far? Are there any other benefits in terms of
productivity you can think of? Note: you need to provide feedback using at
least one of the three free-form arguments ( |
increase_quality |
This is one of the fields we are most interested in.
Please use this argument to tell us how texreg increases the quality
of your work or the quality of your reporting. For example, does the
package generate tables that look more professional than the tables you
used to create manually? Are you using screenreg to improve your
workflow by understanding better how the results of multiple models
compare? Are you using plotreg to visualize and present your
statistical results in a more effective way? Can you think of any other
ways in which texreg is helping you? Note: you need to provide
feedback using at least one of the three free-form arguments
( |
start_using |
(Optional) When did you start using texreg? We are
interested in the approximate time or year as a free-form text argument,
for example |
where_learn |
(Optional) Where or how did you learn about the texreg package? |
contact_details |
(Optional) Tell us how we can contact you in case we would benefit from additional information. This might help us further down the road in compiling an impact case study or a similar report. Don't worry, this information will not be displayed on the website! |
models |
(Optional) Which kinds of statistical models do you use in your
work? For example, |
num_users |
(Optional) How many other texreg users do you know? In
particular, if you are a non-academic user, would you mind telling us how
many other non-academic users you are aware of and how many of them are in
your organization? The more we know, the more convincing our evidence base
will be. This argument accepts |
return.response |
If |
The praise_interactive function asks you 11 questions
interactively on the R console. You can choose to answer or skip them. Some
questions are mandatory but most are optional. After collecting your answers,
it will call the praise function to submit your praise. You can
also choose to use the praise function directly and supply your
answers as arguments. Either way is fine.
Before your praise is submitted, the functions will present an interactive menu and ask if you want to submit the praise now. So do not worry about accidentally submitting feedback.
You can use these functions to praise the texreg package. Funders and academic employers are increasingly interested in seeing evidence for the impact academic research generates. For software, such as texreg, this is very hard to accomplish because the developers are usually disconnected from the users. The consequence is that incentives for developing packages like these are diminishing the more the funders and employers require evidence of impact on society, firms, or policy makers.
The praise and praise_interactive functions are
our attempt at rectifying the situation. With these functions, you can
provide positive feedback to the developers. The praise is saved to a
database on the web server of the package maintainer and subsequently
displayed at https://www.philipleifeld.com/praise/ for other users,
funders, and employers to view. This will also enable the package authors to
compile reports about how texreg is used by academic and non-academic
users to increase their productivity and work quality, for example in the
form of an impact case study for the next round of the UK Research Excellence
Framework (REF).
We need many positive examples of how texreg has an impact on your work. We are especially interested in non-academic users, but welcome feedback from anyone. So please contribute by using the praise function! Tell us how cool this package is and how it has changed your work!
The minimal information we require from you is whether you are an academic or non-academic user, the name of your organization, and some free-form praise (of a general nature, or about how it makes you more productive, or about how it increases the quality of your work or reporting). But there are some additional fields. While we are happy with the basic information, of course we will be happier if we also know your name, how to contact you, what kinds of models you work with, and some other details. Your choice!
Please note that by using the praise or
praise_interactive function you agree that the information you
provide through the function, including your approximate location, is stored
online in a database, displayed on the website of the package author, and
used in reports to funders, employers etc. (This is the whole purpose of it.)
You can contact the package maintainer any time to have your praise removed
within a few days.
If everything works well, no output is returned (but see the
return.response argument to change this). If the submission of the
praise to the maintainer fails, a response object (as defined in the
httr package) will be returned. Should you have any problems, do feel
free to e-mail your praise to the package maintainer directly.
Philip Leifeld
## Not run: praise(academic_user = TRUE, organization = "University of Happy Tables", increase_quality = "Man, I've never seen such pretty tables!") ## End(Not run)## Not run: praise(academic_user = TRUE, organization = "University of Happy Tables", increase_quality = "Man, I've never seen such pretty tables!") ## End(Not run)
texregTable object.Prints a texregTable object.
## S3 method for class 'texregTable' print(x, ...)## S3 method for class 'texregTable' print(x, ...)
x |
A |
... |
Additional arguments for the |
Philip Leifeld
Conversion of R regression output to an ASCII table for display on screen.
screenreg( l, file = NULL, single.row = FALSE, stars = c(0.001, 0.01, 0.05), custom.header = NULL, custom.model.names = NULL, custom.coef.names = NULL, custom.coef.map = NULL, custom.gof.names = NULL, custom.gof.rows = NULL, custom.note = NULL, digits = 2, leading.zero = TRUE, star.symbol = "*", symbol = ".", override.coef = 0, override.se = 0, override.pvalues = 0, override.ci.low = 0, override.ci.up = 0, omit.coef = NULL, reorder.coef = NULL, reorder.gof = NULL, ci.force = FALSE, ci.force.level = 0.95, ci.test = 0, groups = NULL, custom.columns = NULL, custom.col.pos = NULL, column.spacing = 2, outer.rule = "=", inner.rule = "-", ... )screenreg( l, file = NULL, single.row = FALSE, stars = c(0.001, 0.01, 0.05), custom.header = NULL, custom.model.names = NULL, custom.coef.names = NULL, custom.coef.map = NULL, custom.gof.names = NULL, custom.gof.rows = NULL, custom.note = NULL, digits = 2, leading.zero = TRUE, star.symbol = "*", symbol = ".", override.coef = 0, override.se = 0, override.pvalues = 0, override.ci.low = 0, override.ci.up = 0, omit.coef = NULL, reorder.coef = NULL, reorder.gof = NULL, ci.force = FALSE, ci.force.level = 0.95, ci.test = 0, groups = NULL, custom.columns = NULL, custom.col.pos = NULL, column.spacing = 2, outer.rule = "=", inner.rule = "-", ... )
l |
A statistical model or a list of statistical models. Lists of
models can be specified as |
file |
Using this argument, the resulting table is written to a file
rather than to the R prompt. The file name can be specified as a character
string. Writing a table to a file can be useful for working with MS Office
or LibreOffice. For example, using the |
single.row |
By default, a model parameter takes up two lines of the
table: the standard error is listed in parentheses under the coefficient.
This saves a lot of horizontal space on the page and is the default table
format in most academic journals. If |
stars |
The significance levels to be used to draw stars. Between 0 and
4 threshold values can be provided as a numeric vector. For example,
|
custom.header |
An optional named list of multi-column headers that are
placed above the model names. For example,
|
custom.model.names |
A character vector of labels for the models. By
default, the models are named "Model 1", "Model 2", etc. Specifying
|
custom.coef.names |
By default, texreg uses the coefficient names
which are stored in the models. The Sometimes it happens that the same variable has a different name in different models. In this case, the user can use this function to assign identical names. If possible, the rows will then be merged into a single row unless both rows contain values in the same column. Where the argument contains an See also |
custom.coef.map |
The Users must supply a named list of this form:
|
custom.gof.names |
A character vector which is used to replace the
names of the goodness-of-fit statistics at the bottom of the table. The
vector must have the same length as the number of GOF statistics in the
final table. The argument works like the |
custom.gof.rows |
A named list of vectors for new lines at the
beginning of the GOF block of the table. For example, |
custom.note |
With this argument, a replacement text for the
significance note below the table can be provided. If an empty
If the |
digits |
Set the number of decimal places for coefficients, standard
errors and goodness-of-fit statistics. Do not use negative values! The
argument works like the |
leading.zero |
Most journals require leading zeros of coefficients and
standard errors (for example, |
star.symbol |
Alternative characters for the significance stars can be
specified. This is useful if knitr and Markdown are used for HTML
report generation. In Markdown, asterisks or stars are interpreted as
special characters, so they have to be escaped. To make a HTML table
compatible with Markdown, specify |
symbol |
If four threshold values are handed over to the |
override.coef |
Set custom values for the coefficients. New coefficients
are provided as a list of numeric vectors. The list contains vectors of
coefficients for each model. There must be as many vectors of coefficients
as there are models. For example, if there are two models with three model
terms each, the argument could be specified as |
override.se |
Set custom values for the standard errors. New standard
errors are provided as a list of numeric vectors. The list contains vectors
of standard errors for each model. There must be as many vectors of
standard errors as there are models. For example, if there are two models
with three coefficients each, the argument could be specified as
|
override.pvalues |
Set custom values for the p-values. New p-values are
provided as a list of numeric vectors. The list contains vectors of
p-values for each model. There must be as many vectors of p-values as there
are models. For example, if there are two models with three coefficients
each, the argument could be specified as |
override.ci.low |
Set custom lower confidence interval bounds. This
works like the other override arguments, with one exception: if confidence
intervals are provided here and in the |
override.ci.up |
Set custom upper confidence interval bounds. This
works like the other override arguments, with one exception: if confidence
intervals are provided here and in the |
omit.coef |
A character string which is used as a regular expression to
remove coefficient rows from the table. For example, |
reorder.coef |
Reorder the rows of the coefficient block of the
resulting table in a custom way. The argument takes a vector of the same
length as the number of coefficients. For example, if there are three
coefficients, |
reorder.gof |
Reorder the rows of the goodness-of-fit block of the
resulting table in a custom way. The argument takes a vector of the same
length as the number of GOF statistics. For example, if there are three
goodness-of-fit rows, |
ci.force |
Should confidence intervals be used instead of the default
standard errors and p-values? Most models implemented in the texreg
package report standard errors and p-values by default while few models
report confidence intervals. However, the functions in the texreg
package can convert standard errors and into confidence intervals using
z-scores if desired. To enforce confidence intervals instead of standard
errors, the |
ci.force.level |
If the |
ci.test |
If confidence intervals are reported, the |
groups |
This argument can be used to group the rows of the table into
blocks. For example, there could be one block for hypotheses and another
block for control variables. Each group has a heading, and the row labels
within a group are indented. The partitions must be handed over as a list
of named numeric vectors, where each number is a row index and each name is
the heading of the group. Example: |
custom.columns |
An optional list of additional text columns to be
inserted into the coefficient block of the table, for example coefficient
types. The list should contain one or more character vectors with as many
character or numeric elements as there are coefficients/model terms. If the
vectors in the list are named, the names are used as labels in the table
header. For example,
|
custom.col.pos |
An optional integer vector of positions for the columns
given in the |
column.spacing |
The amount of space between any two columns of a table.
By default, two spaces are used. If the tables do not fit on a single page
horizontally, the value can be set to |
outer.rule |
The character which is used to draw the outer horizontal
line above and below a table. If an empty character object is provided
(i.e., |
inner.rule |
The character used to draw the inner horizontal line above
and below a table. If an empty |
... |
Custom options to be passed on to the |
The screenreg function creates text representations of tables
and prints them to the R console. This is an alternative to the
summary function and serves easy model comparison.
Moreover, once a table has been prepared in the R console, it can be later
exported to LaTeX or HTML with little extra effort because the majority of
arguments of the different functions are identical.
Philip Leifeld
Leifeld, Philip (2013). texreg: Conversion of Statistical Model Output in R to LaTeX and HTML Tables. Journal of Statistical Software 55(8): 1-24. doi:10.18637/jss.v055.i08.
Other texreg:
htmlreg(),
huxtablereg(),
knitreg(),
matrixreg(),
plotreg(),
texreg,
wordreg()
# Display models from ?lm: ctl <- c(4.17, 5.58, 5.18, 6.11, 4.50, 4.61, 5.17, 4.53, 5.33, 5.14) trt <- c(4.81, 4.17, 4.41, 3.59, 5.87, 3.83, 6.03, 4.89, 4.32, 4.69) group <- gl(2, 10, 20, labels = c("Ctl", "Trt")) weight <- c(ctl, trt) lm.D9 <- lm(weight ~ group) lm.D90 <- lm(weight ~ group - 1) screenreg(list(lm.D9, lm.D90))# Display models from ?lm: ctl <- c(4.17, 5.58, 5.18, 6.11, 4.50, 4.61, 5.17, 4.53, 5.33, 5.14) trt <- c(4.81, 4.17, 4.41, 3.59, 5.87, 3.83, 6.03, 4.89, 4.32, 4.69) group <- gl(2, 10, 20, labels = c("Ctl", "Trt")) weight <- c(ctl, trt) lm.D9 <- lm(weight ~ group) lm.D90 <- lm(weight ~ group - 1) screenreg(list(lm.D9, lm.D90))
Show method for pretty output of texreg objects.
## S4 method for signature 'texreg' show(object)## S4 method for signature 'texreg' show(object)
object |
The texreg object to display. |
Print the different slots of texreg objects to the screen.
Philip Leifeld
Leifeld, Philip (2013). texreg: Conversion of Statistical Model Output in R to LaTeX and HTML Tables. Journal of Statistical Software 55(8): 1-24. doi:10.18637/jss.v055.i08.
extract, createTexreg,
screenreg
Conversion of R regression output to a LaTeX table.
texreg( l, file = NULL, single.row = FALSE, stars = c(0.001, 0.01, 0.05), custom.header = NULL, custom.model.names = NULL, custom.coef.names = NULL, custom.coef.map = NULL, custom.gof.names = NULL, custom.gof.rows = NULL, custom.note = NULL, digits = 2, leading.zero = TRUE, symbol = "\\cdot", override.coef = 0, override.se = 0, override.pvalues = 0, override.ci.low = 0, override.ci.up = 0, omit.coef = NULL, reorder.coef = NULL, reorder.gof = NULL, ci.force = FALSE, ci.force.level = 0.95, ci.test = 0, groups = NULL, custom.columns = NULL, custom.col.pos = NULL, bold = 0, center = TRUE, caption = "Statistical models", caption.above = FALSE, label = "table:coefficients", booktabs = FALSE, dcolumn = FALSE, siunitx = FALSE, lyx = FALSE, sideways = FALSE, longtable = FALSE, threeparttable = FALSE, use.packages = TRUE, table = TRUE, tabular = TRUE, no.margin = FALSE, fontsize = NULL, scalebox = NULL, float.pos = "", ... )texreg( l, file = NULL, single.row = FALSE, stars = c(0.001, 0.01, 0.05), custom.header = NULL, custom.model.names = NULL, custom.coef.names = NULL, custom.coef.map = NULL, custom.gof.names = NULL, custom.gof.rows = NULL, custom.note = NULL, digits = 2, leading.zero = TRUE, symbol = "\\cdot", override.coef = 0, override.se = 0, override.pvalues = 0, override.ci.low = 0, override.ci.up = 0, omit.coef = NULL, reorder.coef = NULL, reorder.gof = NULL, ci.force = FALSE, ci.force.level = 0.95, ci.test = 0, groups = NULL, custom.columns = NULL, custom.col.pos = NULL, bold = 0, center = TRUE, caption = "Statistical models", caption.above = FALSE, label = "table:coefficients", booktabs = FALSE, dcolumn = FALSE, siunitx = FALSE, lyx = FALSE, sideways = FALSE, longtable = FALSE, threeparttable = FALSE, use.packages = TRUE, table = TRUE, tabular = TRUE, no.margin = FALSE, fontsize = NULL, scalebox = NULL, float.pos = "", ... )
l |
A statistical model or a list of statistical models. Lists of
models can be specified as |
file |
Using this argument, the resulting table is written to a file
rather than to the R prompt. The file name can be specified as a character
string. Writing a table to a file can be useful for working with MS Office
or LibreOffice. For example, using the |
single.row |
By default, a model parameter takes up two lines of the
table: the standard error is listed in parentheses under the coefficient.
This saves a lot of horizontal space on the page and is the default table
format in most academic journals. If |
stars |
The significance levels to be used to draw stars. Between 0 and
4 threshold values can be provided as a numeric vector. For example,
|
custom.header |
An optional named list of multi-column headers that are
placed above the model names. For example,
|
custom.model.names |
A character vector of labels for the models. By
default, the models are named "Model 1", "Model 2", etc. Specifying
|
custom.coef.names |
By default, texreg uses the coefficient names
which are stored in the models. The Sometimes it happens that the same variable has a different name in different models. In this case, the user can use this function to assign identical names. If possible, the rows will then be merged into a single row unless both rows contain values in the same column. Where the argument contains an See also |
custom.coef.map |
The Users must supply a named list of this form:
|
custom.gof.names |
A character vector which is used to replace the
names of the goodness-of-fit statistics at the bottom of the table. The
vector must have the same length as the number of GOF statistics in the
final table. The argument works like the |
custom.gof.rows |
A named list of vectors for new lines at the
beginning of the GOF block of the table. For example, |
custom.note |
With this argument, a replacement text for the
significance note below the table can be provided. If an empty
If the |
digits |
Set the number of decimal places for coefficients, standard
errors and goodness-of-fit statistics. Do not use negative values! The
argument works like the |
leading.zero |
Most journals require leading zeros of coefficients and
standard errors (for example, |
symbol |
If four threshold values are handed over to the |
override.coef |
Set custom values for the coefficients. New coefficients
are provided as a list of numeric vectors. The list contains vectors of
coefficients for each model. There must be as many vectors of coefficients
as there are models. For example, if there are two models with three model
terms each, the argument could be specified as |
override.se |
Set custom values for the standard errors. New standard
errors are provided as a list of numeric vectors. The list contains vectors
of standard errors for each model. There must be as many vectors of
standard errors as there are models. For example, if there are two models
with three coefficients each, the argument could be specified as
|
override.pvalues |
Set custom values for the p-values. New p-values are
provided as a list of numeric vectors. The list contains vectors of
p-values for each model. There must be as many vectors of p-values as there
are models. For example, if there are two models with three coefficients
each, the argument could be specified as |
override.ci.low |
Set custom lower confidence interval bounds. This
works like the other override arguments, with one exception: if confidence
intervals are provided here and in the |
override.ci.up |
Set custom upper confidence interval bounds. This
works like the other override arguments, with one exception: if confidence
intervals are provided here and in the |
omit.coef |
A character string which is used as a regular expression to
remove coefficient rows from the table. For example, |
reorder.coef |
Reorder the rows of the coefficient block of the
resulting table in a custom way. The argument takes a vector of the same
length as the number of coefficients. For example, if there are three
coefficients, |
reorder.gof |
Reorder the rows of the goodness-of-fit block of the
resulting table in a custom way. The argument takes a vector of the same
length as the number of GOF statistics. For example, if there are three
goodness-of-fit rows, |
ci.force |
Should confidence intervals be used instead of the default
standard errors and p-values? Most models implemented in the texreg
package report standard errors and p-values by default while few models
report confidence intervals. However, the functions in the texreg
package can convert standard errors and into confidence intervals using
z-scores if desired. To enforce confidence intervals instead of standard
errors, the |
ci.force.level |
If the |
ci.test |
If confidence intervals are reported, the |
groups |
This argument can be used to group the rows of the table into
blocks. For example, there could be one block for hypotheses and another
block for control variables. Each group has a heading, and the row labels
within a group are indented. The partitions must be handed over as a list
of named numeric vectors, where each number is a row index and each name is
the heading of the group. Example: |
custom.columns |
An optional list of additional text columns to be
inserted into the coefficient block of the table, for example coefficient
types. The list should contain one or more character vectors with as many
character or numeric elements as there are coefficients/model terms. If the
vectors in the list are named, the names are used as labels in the table
header. For example,
|
custom.col.pos |
An optional integer vector of positions for the columns
given in the |
bold |
The p-value threshold below which the coefficient shall be
formatted in a bold font. For example, |
center |
Should the table be horizontally aligned at the center of the page? |
caption |
Set the caption of the table. |
caption.above |
Should the caption of the table be placed above the table? By default, it is placed below the table. |
label |
Set the label of the |
booktabs |
Use the booktabs LaTeX package to get thick horizontal rules in the output table (recommended). |
dcolumn |
Use the dcolumn LaTeX package to get a nice alignment of
the coefficients at the decimal separator (recommended for use with the
|
siunitx |
Use the siunitx LaTeX package to get a nice alignment of
the coefficients at the decimal separator (recommended for use with the
|
lyx |
|
sideways |
If |
longtable |
If |
threeparttable |
If |
use.packages |
If this argument is set to |
table |
By default, |
tabular |
By default, the table contents are wrapped in a |
no.margin |
In order to save space, inner margins of tables can be switched off. |
fontsize |
The |
scalebox |
The |
float.pos |
This argument specifies where the table should be located on
the page or in the document. By default, no floating position is specified,
and LaTeX takes care of the position automatically. Possible values include
|
... |
Custom options to be passed on to the |
The texreg function creates LaTeX code for inclusion in a LaTeX
document or for usage with Sweave or knitr, based on a list of
statistical models.
A character object with a regression table and LaTeX markup.
The object has an additional "texregTable" class identifier, which
causes the object to be formatted nicely on screen when printed.
Philip Leifeld
Leifeld, Philip (2013). texreg: Conversion of Statistical Model Output in R to LaTeX and HTML Tables. Journal of Statistical Software 55(8): 1-24. doi:10.18637/jss.v055.i08.
Other texreg:
htmlreg(),
huxtablereg(),
knitreg(),
matrixreg(),
plotreg(),
screenreg(),
wordreg()
# Linear mixed-effects models library("nlme") model.1 <- lme(distance ~ age, data = Orthodont, random = ~ 1) model.2 <- lme(distance ~ age + Sex, data = Orthodont, random = ~ 1) texreg(list(model.1, model.2), booktabs = TRUE, dcolumn = TRUE) # Ordinary least squares model (example from the 'lm' help file) ctl <- c(4.17,5.58,5.18,6.11,4.50,4.61,5.17,4.53,5.33,5.14) trt <- c(4.81,4.17,4.41,3.59,5.87,3.83,6.03,4.89,4.32,4.69) group <- gl(2,10,20, labels = c("Ctl","Trt")) weight <- c(ctl, trt) lm.D9 <- lm(weight ~ group) table.string <- texreg(lm.D9, return.string = TRUE) cat(table.string)# Linear mixed-effects models library("nlme") model.1 <- lme(distance ~ age, data = Orthodont, random = ~ 1) model.2 <- lme(distance ~ age + Sex, data = Orthodont, random = ~ 1) texreg(list(model.1, model.2), booktabs = TRUE, dcolumn = TRUE) # Ordinary least squares model (example from the 'lm' help file) ctl <- c(4.17,5.58,5.18,6.11,4.50,4.61,5.17,4.53,5.33,5.14) trt <- c(4.81,4.17,4.41,3.59,5.87,3.83,6.03,4.89,4.32,4.69) group <- gl(2,10,20, labels = c("Ctl","Trt")) weight <- c(ctl, trt) lm.D9 <- lm(weight ~ group) table.string <- texreg(lm.D9, return.string = TRUE) cat(table.string)
An S4 class to represent a statistical model as a texreg object.
A texreg object stores details about a statistical model. It
can be used for creating regression tables using screenreg,
texreg, and similar functions.
coef.namesThe covariate names.
coefThe coefficients.
seThe standard errors.
pvaluesThe p-values.
ci.lowThe lower bounds of the confidence intervals.
ci.upThe upper bounds of the confidence intervals.
gof.namesThe names of the goodness-of-fit statistics.
gofThe goodness-of-fit statistics.
gof.decimalA vector describing for each GOF statistic whether it is a
decimal value (TRUE) or an integer value (FALSE).
model.nameAn optional model name. Can be of length zero.
Philip Leifeld
Leifeld, Philip (2013). texreg: Conversion of Statistical Model Output in R to LaTeX and HTML Tables. Journal of Statistical Software 55(8): 1-24. doi:10.18637/jss.v055.i08.
Export regression output to an MS Word file.
wordreg( l, file = NULL, single.row = FALSE, stars = c(0.001, 0.01, 0.05), custom.model.names = NULL, custom.coef.names = NULL, custom.coef.map = NULL, custom.gof.names = NULL, custom.gof.rows = NULL, digits = 2, leading.zero = TRUE, star.symbol = "*", symbol = ".", override.coef = 0, override.se = 0, override.pvalues = 0, override.ci.low = 0, override.ci.up = 0, omit.coef = NULL, reorder.coef = NULL, reorder.gof = NULL, ci.force = FALSE, ci.force.level = 0.95, ci.test = 0, groups = NULL, custom.columns = NULL, custom.col.pos = NULL, ... )wordreg( l, file = NULL, single.row = FALSE, stars = c(0.001, 0.01, 0.05), custom.model.names = NULL, custom.coef.names = NULL, custom.coef.map = NULL, custom.gof.names = NULL, custom.gof.rows = NULL, digits = 2, leading.zero = TRUE, star.symbol = "*", symbol = ".", override.coef = 0, override.se = 0, override.pvalues = 0, override.ci.low = 0, override.ci.up = 0, omit.coef = NULL, reorder.coef = NULL, reorder.gof = NULL, ci.force = FALSE, ci.force.level = 0.95, ci.test = 0, groups = NULL, custom.columns = NULL, custom.col.pos = NULL, ... )
l |
A statistical model or a list of statistical models. Lists of
models can be specified as |
file |
Using this argument, the resulting table is written to a file
rather than to the R prompt. The file name can be specified as a character
string. Writing a table to a file can be useful for working with MS Office
or LibreOffice. For example, using the |
single.row |
By default, a model parameter takes up two lines of the
table: the standard error is listed in parentheses under the coefficient.
This saves a lot of horizontal space on the page and is the default table
format in most academic journals. If |
stars |
The significance levels to be used to draw stars. Between 0 and
4 threshold values can be provided as a numeric vector. For example,
|
custom.model.names |
A character vector of labels for the models. By
default, the models are named "Model 1", "Model 2", etc. Specifying
|
custom.coef.names |
By default, texreg uses the coefficient names
which are stored in the models. The Sometimes it happens that the same variable has a different name in different models. In this case, the user can use this function to assign identical names. If possible, the rows will then be merged into a single row unless both rows contain values in the same column. Where the argument contains an See also |
custom.coef.map |
The Users must supply a named list of this form:
|
custom.gof.names |
A character vector which is used to replace the
names of the goodness-of-fit statistics at the bottom of the table. The
vector must have the same length as the number of GOF statistics in the
final table. The argument works like the |
custom.gof.rows |
A named list of vectors for new lines at the
beginning of the GOF block of the table. For example, |
digits |
Set the number of decimal places for coefficients, standard
errors and goodness-of-fit statistics. Do not use negative values! The
argument works like the |
leading.zero |
Most journals require leading zeros of coefficients and
standard errors (for example, |
star.symbol |
Alternative characters for the significance stars can be
specified. This is useful if knitr and Markdown are used for HTML
report generation. In Markdown, asterisks or stars are interpreted as
special characters, so they have to be escaped. To make a HTML table
compatible with Markdown, specify |
symbol |
If four threshold values are handed over to the |
override.coef |
Set custom values for the coefficients. New coefficients
are provided as a list of numeric vectors. The list contains vectors of
coefficients for each model. There must be as many vectors of coefficients
as there are models. For example, if there are two models with three model
terms each, the argument could be specified as |
override.se |
Set custom values for the standard errors. New standard
errors are provided as a list of numeric vectors. The list contains vectors
of standard errors for each model. There must be as many vectors of
standard errors as there are models. For example, if there are two models
with three coefficients each, the argument could be specified as
|
override.pvalues |
Set custom values for the p-values. New p-values are
provided as a list of numeric vectors. The list contains vectors of
p-values for each model. There must be as many vectors of p-values as there
are models. For example, if there are two models with three coefficients
each, the argument could be specified as |
override.ci.low |
Set custom lower confidence interval bounds. This
works like the other override arguments, with one exception: if confidence
intervals are provided here and in the |
override.ci.up |
Set custom upper confidence interval bounds. This
works like the other override arguments, with one exception: if confidence
intervals are provided here and in the |
omit.coef |
A character string which is used as a regular expression to
remove coefficient rows from the table. For example, |
reorder.coef |
Reorder the rows of the coefficient block of the
resulting table in a custom way. The argument takes a vector of the same
length as the number of coefficients. For example, if there are three
coefficients, |
reorder.gof |
Reorder the rows of the goodness-of-fit block of the
resulting table in a custom way. The argument takes a vector of the same
length as the number of GOF statistics. For example, if there are three
goodness-of-fit rows, |
ci.force |
Should confidence intervals be used instead of the default
standard errors and p-values? Most models implemented in the texreg
package report standard errors and p-values by default while few models
report confidence intervals. However, the functions in the texreg
package can convert standard errors and into confidence intervals using
z-scores if desired. To enforce confidence intervals instead of standard
errors, the |
ci.force.level |
If the |
ci.test |
If confidence intervals are reported, the |
groups |
This argument can be used to group the rows of the table into
blocks. For example, there could be one block for hypotheses and another
block for control variables. Each group has a heading, and the row labels
within a group are indented. The partitions must be handed over as a list
of named numeric vectors, where each number is a row index and each name is
the heading of the group. Example: |
custom.columns |
An optional list of additional text columns to be
inserted into the coefficient block of the table, for example coefficient
types. The list should contain one or more character vectors with as many
character or numeric elements as there are coefficients/model terms. If the
vectors in the list are named, the names are used as labels in the table
header. For example,
|
custom.col.pos |
An optional integer vector of positions for the columns
given in the |
... |
Custom options to be passed on to the |
The wordreg function creates a Microsoft Word document with the
requested table.
Vincent Arel-Bundock
Other texreg:
htmlreg(),
huxtablereg(),
knitreg(),
matrixreg(),
plotreg(),
screenreg(),
texreg
## Not run: # Use models from ?lm: ctl <- c(4.17, 5.58, 5.18, 6.11, 4.50, 4.61, 5.17, 4.53, 5.33, 5.14) trt <- c(4.81, 4.17, 4.41, 3.59, 5.87, 3.83, 6.03, 4.89, 4.32, 4.69) group <- gl(2, 10, 20, labels = c("Ctl", "Trt")) weight <- c(ctl, trt) lm.D9 <- lm(weight ~ group) lm.D90 <- lm(weight ~ group - 1) wordreg(list(lm.D9, lm.D90), file = "testfile.doc") unlink("testfile.doc") ## End(Not run)## Not run: # Use models from ?lm: ctl <- c(4.17, 5.58, 5.18, 6.11, 4.50, 4.61, 5.17, 4.53, 5.33, 5.14) trt <- c(4.81, 4.17, 4.41, 3.59, 5.87, 3.83, 6.03, 4.89, 4.32, 4.69) group <- gl(2, 10, 20, labels = c("Ctl", "Trt")) weight <- c(ctl, trt) lm.D9 <- lm(weight ~ group) lm.D90 <- lm(weight ~ group - 1) wordreg(list(lm.D9, lm.D90), file = "testfile.doc") unlink("testfile.doc") ## End(Not run)