Extract coefficients and GOF measures from a statistical object.
extract(model, ...)# S4 method for aftreg
extract(model, include.loglik = TRUE,
include.lr = TRUE, include.nobs = TRUE, include.events = TRUE,
include.trisk = TRUE, ...)
# S4 method for Arima
extract(model, include.pvalues = FALSE,
include.aic = TRUE, include.loglik = TRUE, ...)
# S4 method for ARIMA
extract(model, include.pvalues = FALSE,
include.aic = TRUE, include.aicc = TRUE, include.bic = TRUE,
include.loglik = TRUE, ...)
# S4 method for averaging
extract(model, use.ci = FALSE,
adjusted.se = FALSE, include.nobs = TRUE, ...)
# S4 method for 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 betamfx
extract(model, include.pseudors = TRUE,
include.loglik = TRUE, include.nobs = TRUE, ...)
# S4 method for betaor
extract(model, include.pseudors = TRUE,
include.loglik = TRUE, include.nobs = TRUE, ...)
# S4 method for betareg
extract(model, include.precision = TRUE,
include.pseudors = TRUE, include.loglik = TRUE,
include.nobs = TRUE, ...)
# S4 method for brglm
extract(model, include.aic = TRUE,
include.bic = TRUE, include.loglik = TRUE,
include.deviance = TRUE, include.nobs = TRUE, ...)
# S4 method for btergm
extract(model, level = 0.95,
include.nobs = TRUE, ...)
# S4 method for censReg
extract(model, include.aic = TRUE,
include.bic = TRUE, include.loglik = TRUE,
include.nobs = TRUE, ...)
# S4 method for clm
extract(model, include.thresholds = TRUE,
include.aic = TRUE, include.bic=TRUE, include.loglik = TRUE,
include.nobs = TRUE, ...)
# S4 method for 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 clogit
extract(model, include.aic = TRUE,
include.rsquared = TRUE, include.maxrs = TRUE,
include.events = TRUE, include.nobs = TRUE,
include.missings = TRUE, ...)
# S4 method for coeftest
extract(model, ...)
# S4 method for 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 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 dynlm
extract(model, include.rsquared = TRUE,
include.adjrs = TRUE, include.nobs = TRUE,
include.fstatistic = FALSE, include.rmse = TRUE, ...)
# S4 method for ergm
extract(model, include.aic = TRUE,
include.bic = TRUE, include.loglik = TRUE, ...)
# S4 method for ergmm
extract(model, include.bic = TRUE, ...)
# S4 method for ets
extract(model, include.pvalues = FALSE,
include.aic = TRUE, include.aicc = TRUE, include.bic = TRUE,
include.loglik = TRUE, ...)
# S4 method for felm
extract(model, include.nobs = TRUE,
include.rsquared = TRUE, include.adjrs = TRUE,
include.fstatistic = FALSE, ...)
# S4 method for fGARCH
extract(model, include.nobs = TRUE,
include.aic = TRUE, include.loglik = TRUE, ...)
# S4 method for forecast
extract(model, ...)
# S4 method for 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 gamlss
extract(model, robust = FALSE,
include.nobs = TRUE, include.nagelkerke = TRUE,
include.gaic = TRUE, ...)
# S4 method for gee
extract(model, robust = TRUE,
include.dispersion = TRUE, include.nobs = TRUE, ...)
# S4 method for geeglm
extract(model, include.scale = TRUE,
include.correlation = TRUE, include.nobs = TRUE, ...)
# S4 method for gel
extract(model, include.obj.fcn = TRUE,
include.overidentification = FALSE, include.nobs = TRUE,
overIdentTest = c("LR", "LM", "J "), ...)
# S4 method for glm
extract(model, include.aic = TRUE,
include.bic = TRUE, include.loglik = TRUE,
include.deviance = TRUE, include.nobs = TRUE, ...)
# S4 method for 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 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 glmmPQL
extract(model, include.aic = TRUE,
include.bic = TRUE, include.loglik = TRUE,
include.nobs = TRUE, include.groups = TRUE,
include.variance = FALSE, ...)
# S4 method for glmrob
extract(model, include.nobs = TRUE, ...)
# S4 method for gls
extract(model, include.aic = TRUE,
include.bic = TRUE, include.loglik = TRUE,
include.nobs = TRUE, ...)
# S4 method for gmm
extract(model, include.obj.fcn = TRUE,
include.overidentification = FALSE, include.nobs = TRUE, ...)
# S4 method for 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 hurdle
extract(model, beside = FALSE,
include.count = TRUE, include.zero = TRUE, include.aic = TRUE,
include.loglik = TRUE, include.nobs = TRUE, ...)
# S4 method for ivreg
extract(model, include.rsquared = TRUE,
include.adjrs = TRUE, include.nobs = TRUE,
include.fstatistic = FALSE, include.rmse = TRUE, ...)
# S4 method for lm
extract(model, include.rsquared = TRUE,
include.adjrs = TRUE, include.nobs = TRUE,
include.fstatistic = FALSE, include.rmse = TRUE, ...)
# S4 method for lme
extract(model, include.aic = TRUE,
include.bic = TRUE, include.loglik = TRUE,
include.nobs = TRUE, include.groups = TRUE,
include.variance = FALSE, ...)
# S4 method for 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 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 lmrob
extract(model, include.nobs = TRUE, ...)
# S4 method for lnam
extract(model, include.rsquared = TRUE,
include.adjrs = TRUE, include.aic = TRUE, include.bic = TRUE,
include.loglik = TRUE, ...)
# S4 method for logitmfx
extract(model, include.nobs = TRUE,
include.loglik = TRUE, include.deviance = TRUE,
include.aic = TRUE, include.bic = TRUE, ...)
# S4 method for logitor
extract(model, include.nobs = TRUE,
include.loglik = TRUE, include.deviance = TRUE,
include.aic = TRUE, include.bic = TRUE, ...)
# S4 method for 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 lrm
extract(model, include.pseudors = TRUE,
include.lr = TRUE, include.nobs = TRUE, ...)
# S4 method for maBina
extract(model, ...)
# S4 method for mer
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 mnlogit
extract(model, include.aic = TRUE,
include.loglik = TRUE, include.nobs = TRUE,
include.groups = TRUE, include.intercept = TRUE,
include.iterations = FALSE, beside = FALSE, ...)
# S4 method for mlogit
extract(model, include.aic = TRUE,
include.loglik = TRUE, include.nobs = TRUE, ...)
# S4 method for model.selection
extract(model, include.loglik = TRUE,
include.aicc = TRUE, include.delta = TRUE,
include.weight = TRUE, include.nobs = TRUE, ...)
# S4 method for mtergm
extract(model, include.nobs = TRUE,
include.aic = TRUE, include.bic = TRUE, include.loglik = TRUE,
...)
# S4 method for multinom
extract(model, include.pvalues = TRUE,
include.aic = TRUE, include.bic = TRUE, include.loglik = TRUE,
include.deviance = TRUE, include.nobs = TRUE,
levels = model$lev, beside = TRUE, ...)
# S4 method for negbin
extract(model, include.aic = TRUE,
include.bic = TRUE, include.loglik = TRUE,
include.deviance = TRUE, include.nobs = TRUE, ...)
# S4 method for negbinirr
extract(model, include.nobs = TRUE,
include.loglik = TRUE, include.deviance = TRUE,
include.aic = TRUE, include.bic = TRUE, ...)
# S4 method for negbinmfx
extract(model, include.nobs = TRUE,
include.loglik = TRUE, include.deviance = TRUE,
include.aic = TRUE, include.bic = TRUE, ...)
# S4 method for netlogit
extract(model, include.aic = TRUE,
include.bic = TRUE, include.deviance = TRUE,
include.nobs = TRUE, ...)
# S4 method for nlme
extract(model, include.aic = TRUE,
include.bic = TRUE, include.loglik = TRUE,
include.nobs = TRUE, include.groups = TRUE,
include.variance = FALSE, ...)
# S4 method for 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 ols
extract(model, include.nobs = TRUE,
include.rsquared = TRUE, include.adjrs = TRUE,
include.fstatistic = FALSE, include.lr = TRUE, ...)
# S4 method for pgmm
extract(model, include.nobs = TRUE,
include.sargan = TRUE, include.wald = TRUE, ...)
# S4 method for phreg
extract(model, include.loglik = TRUE,
include.lr = TRUE, include.nobs = TRUE, include.events = TRUE,
include.trisk = TRUE, ...)
# S4 method for plm
extract(model, include.rsquared = TRUE,
include.adjrs = TRUE, include.nobs = TRUE, ...)
# S4 method for pmg
extract(model, include.nobs = TRUE, ...)
# S4 method for poissonirr
extract(model, include.nobs = TRUE,
include.loglik = TRUE, include.deviance = TRUE,
include.aic = TRUE, include.bic = TRUE, ...)
# S4 method for poissonmfx
extract(model, include.nobs = TRUE,
include.loglik = TRUE, include.deviance = TRUE,
include.aic = TRUE, include.bic = TRUE, ...)
# S4 method for polr
extract(model, include.thresholds = FALSE,
include.aic = TRUE, include.bic = TRUE, include.loglik = TRUE,
include.deviance = TRUE, include.nobs = TRUE, ...)
# S4 method for probitmfx
extract(model, include.nobs = TRUE,
include.loglik = TRUE, include.deviance = TRUE,
include.aic = TRUE, include.bic = TRUE, ...)
# S4 method for rem.dyad
extract(model, include.nvertices = TRUE,
include.events = TRUE, include.aic = TRUE,
include.aicc = TRUE, include.bic = TRUE, ...)
# S4 method for rlm
extract(model, include.nobs = TRUE, ...)
# S4 method for rq
extract(model, include.nobs = TRUE,
include.percentile = TRUE, ...)
# S4 method for sarlm
extract(model, include.nobs = TRUE,
include.loglik = TRUE, include.aic = TRUE, include.lr = TRUE,
include.wald = TRUE, ...)
# S4 method for sclm
extract(model, include.thresholds = TRUE,
include.aic = TRUE, include.bic = TRUE, include.loglik = TRUE,
include.nobs = TRUE, ...)
# S4 method for 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 sienaFit
extract(model, include.iterations = TRUE,
...)
# S4 method for simex
extract(model, jackknife = TRUE,
include.nobs = TRUE, ...)
# S4 method for 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 survreg
extract(model, include.aic = TRUE,
include.bic = TRUE, include.loglik = TRUE,
include.deviance = TRUE, include.nobs = TRUE, ...)
# S4 method for survreg.penal
extract(model, include.aic = TRUE,
include.bic = TRUE, include.loglik = TRUE,
include.deviance = TRUE, include.nobs = TRUE, ...)
# S4 method for svyglm
extract(model, include.aic = FALSE,
include.bic = FALSE, include.loglik = FALSE,
include.deviance = TRUE, include.dispersion = TRUE,
include.nobs = TRUE, ...)
# S4 method for systemfit
extract(model, include.rsquared = TRUE,
include.adjrs = TRUE, include.nobs = TRUE, beside = FALSE,
include.suffix = FALSE, ...)
# S4 method for texreg
extract(model, ...)
# S4 method for 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 vglm
extract(model, include.loglik = TRUE,
include.df = TRUE, include.nobs = TRUE, ...)
# S4 method for weibreg
extract(model, include.loglik = TRUE,
include.lr = TRUE, include.nobs = TRUE,
include.events = TRUE, include.trisk = TRUE, ...)
# S4 method for wls
extract(model, include.nobs = TRUE, ...)
# S4 method for zelig
extract(model, include.aic = TRUE,
include.bic = TRUE, include.loglik = TRUE,
include.deviance = TRUE, include.nobs = TRUE,
include.rsquared = TRUE, include.adjrs = TRUE,
include.fstatistic = TRUE, ...)
# S4 method for Zelig
extract(model, ...)
# S4 method for zeroinfl
extract(model, beside = FALSE,
include.count = TRUE, include.zero = TRUE, include.aic = TRUE,
include.loglik = TRUE, include.nobs = TRUE, ...)
A statistical model object.
If available: use adjusted rather than default standard errors?
If available: should the model terms be arranged below each other or beside each other? For example, in a stergm model, the formation and dissolution coefficients can be arranged in two columns of the table.
If available: should the adjusted R-squared be reported?
If available: should Akaike's information criterion (AIC) be reported?
If available: should AICc be reported? This is a version of AIC with a correction for finite sample sizes.
If available: should the area under the curve (AUC) be reported?
If available: should the Bayesian information criterion (BIC) be reported?
If available: should the total, right-censored, left-censored, and uncensored number of observations be reported?
If available: should the correlation parameter alpha and its standard error be reported (for geeglm models)?
If available: should the count model of a zero-inflated or hurdle regression be included in the coefficients block (before the zero-inflation or zero hurdle model)?
If available: should the delta statistic be included?
If available: should the deviance explained be reported?
If available: should the deviance be reported?
If available: should the degrees of freedom be reported?
If available: should the deviance information criterion (DIC) be reported?
If available: should the dispersion or scale parameter be reported?
If available: should the coefficients for the dissolution phase in a STERGM be reported?
If available: should the error terms of a sample selection model be reported?
If available: should the number of events be reported (in survival models)?
If available: should the coefficients for the formation phase in a STERGM be reported?
If available: should the F statistic be reported?
If available: should the Generalized Akaike's information criterion (GAIC) be reported?
If available: should the Gini coefficient be reported?
If available: should the GCV score be reported (in GAMs)?
If available: should the number of groups in a mixed-effects model (or k
alternatives in a multinomial choice model) be reported?
If available: should the intercept be included in the GOF block?
If available: should the number of iterations be included?
If available: should the log-likelihood be reported?
If available: should the log loss be reported?
If available: should the likelihood ratio test be reported?
If available: should the maximum possible R-squared be reported?
If available: should the mean per-class error be reported?
If available: should the number of missing observations be reported (in survival models)?
If available: should the mean square error be reported?
If available: should Nagelkerke's R-squared be reported?
If available: should the number of observations be reported?
If available: should the number of smooth terms be reported (in GAMs)?
If available: should the number of vertices be reported in a statistical network model?
If available: should the value of the objective function (= criterion function) be reported (for gel
and gmm
objects)? More precisely, this returns E(g)var(g)^{-1}E(g)
.
If available: should the outcome component of a sample selection model be reported?
If available: should the J-test for overidentification be reported (for gel
and gmm
objects)?
If available: should the percentile (tau) be reported?
If available: should the precision estimates of a betareg fit (the phi coefficients) be reported as part of the coefficients block?
If available: should the pseudo R-squared be reported?
If available: should the p values be reported (naive p values are not recommended for lme4 models, but see also the mcmc.pvalues
argument)?
If available: should the root-mean-square error (= residual standard deviation) be reported?
If available: should R-squared be reported?
If available: should the Sargan test be reported?
If available: should the scale parameter gamma and its standard error be reported (for geeglm models)?
If available: should the selection component of a sample selection model be reported?
If available: should the smooth terms of a GAM be reported? 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).
If available: include the name of the current model in parentheses after each model term (instead of before the model term).
If available: include tau in linear quantile mixed models?
If available: should the threshold parameters (that is, the intercepts for the class boundaries) be reported in ordinal models?
If available: should the total time at risk be reported (in event-history models)?
If available: should group variances be reported?
If available: should the Wald statistic be included?
If available: should the weight be included?
If available: should the zero-inflation model of a zero-inflated regression or the zero hurdle model of a hurdle regression be included in the coefficients block (after the count model)?
If available: should the Cox proportional hazards assumption be tested (resulting in a p value indicating whether the proportional hazards assumption of the model is violated)?
If available: use Jackknife variance instead of Asymptotic variance.
Confidence level (1 - alpha
) for computing confidence intervals.
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.
The method used to compute confidence intervals or p values. In lme4 models, the default value "naive"
computes naive p values while the other methods compute confidence intervals using the confint
function.
In linear mixed effects models: the MCMC sample size or number of bootstrapping replications on the basis of which confidence intervals are computed (only if the method
argument does not specify "naive"
, which is the default behavior). Note: large values may take considerable computing time.
If available: which test statistics should be included in an overidentification test (for gel
and gmm
objects)?
Include prefix before the label of the coefficient in order to identify the current model component.
If available: report robust instead of naive standard errors.
If available: report standardized coefficients instead of raw coefficients?
Use confidence intervals rather than standard errors.
Custom parameters which are handed over to subroutines.
aftreg
An extract method for aftreg objects from the eha package.
Arima
An extract method for Arima objects from the stats package.
ARIMA
An extract method for ARIMA objects from the forecast package.
averaging
An extract method for averaging objects from the MuMIn package.
bam
An extract method for bam objects from the mgcv package.
betamfx
An extract method for betamfx objects from the mfx package.
betaor
An extract method for betaor objects from the mfx package.
betareg
An extract method for betareg objects from the betareg package.
brglm
An extract method for brglm objects from the brglm package.
btergm
An extract method for btergm objects from the xergm package.
censReg
An extract method for censReg objects from the censReg package.
clm
An extract method for clm objects from the ordinal package.
clmm
An extract method for clmm objects from the ordinal package.
clogit
An extract method for clogit objects from the survival package.
coeftest
An extract method for coeftest objects from the lmtest package.
coxph
An extract method for coxph objects from the survival package.
coxph.penal
An extract method for coxph.penal objects from the survival package.
dynlm
An extract method for dynlm objects from the dynlm package.
ergm
An extract method for ergm objects from the ergm package.
ergmm
An extract method for ergmm objects from the latentnet package.
ets
An extract method for ets objects from the forecast package.
felm
An extract method for felm objects from the lfe package.
fGARCH
An extract method for fGARCH objects from the fGarch package.
forecast
An extract method for forecast objects from the forecast package.
gam
An extract method for gam objects from the mgcv package.
gamlss
An extract method for gamlss objects from the gamlss package.
gee
An extract method for gee objects from the gee package.
geeglm
An extract method for geeglm objects from the geepack package.
gel
An extract method for gel objects from the gmm package.
glm
An extract method for glm objects from the stats package.
glmerMod
An extract method for glmerMod objects from the (old) lme4 package.
glmmadmb
An extract method for glmmadmb objects from the glmmADMB package.
glmmPQL
An extract method for glmmPQL objects from the MASS package.
glmrob
An extract method for glmrob objects from the robustbase package.
gls
An extract method for gls objects from the nlme package.
gmm
An extract method for gmm objects from the gmm package.
H2OBinomialModel
An extract method for H2OBinomialModel objects from the h2o package.
hurdle
An extract method for hurdle objects from the pscl package.
ivreg
An extract method for ivreg objects from the AER package.
lm
An extract method for lm objects from the stats package.
lme
An extract method for lme objects from the nlme package.
lme4
An extract method for lme4 objects from the lme4 package.
lmerMod
An extract method for lmerMod objects from the (old) lme4 package.
lmrob
An extract method for lmrob objects from the robustbase package.
lnam
An extract method for lnam objects from the sna package.
logitmfx
An extract method for logitmfx objects from the mfx package.
logitor
An extract method for logitor objects from the mfx package.
lqmm
An extract method for lqmm objects from the lqmm package.
lrm
An extract method for lrm objects from the Design or rms package.
maBina
An extract method for maBina objects from the erer package.
mer
An extract method for mer objects from the (old) lme4 package.
mlogit
An extract method for mlogit objects from the mlogit package.
mnlogit
An extract method for mnlogit objects from the mnlogit package.
model.selection
An extract method for model.selection objects from the MuMIn package.
mtergm
An extract method for mtergm objects from the btergm package.
multinom
An extract method for multinom objects from the nnet package.
negbin
An extract method for negbin objects from the MASS package.
negbinirr
An extract method for negbinirr objects from the mfx package.
negbinmfx
An extract method for negbinmfx objects from the mfx package.
netlogit
An extract method for netlogit objects from the sna package.
nlme
An extract method for nlme objects from the nlme package.
nlmerMod
An extract method for nlmerMod objects from the (old) lme4 package.
ols
An extract method for ols objects from the rms package.
pgmm
An extract method for pgmm objects from the plm package.
phreg
An extract method for phreg objects from the eha package.
plm
An extract method for plm objects from the plm package.
pmg
An extract method for pmg objects from the plm package.
poissonirr
An extract method for poissonirr objects from the mfx package.
poissonmfx
An extract method for poissonmfx objects from the mfx package.
polr
An extract method for polr objects from the MASS package.
probitmfx
An extract method for probitmfx objects from the mfx package.
rem.dyad
An extract method for rem.dyad objects from the relevent package.
rlm
An extract method for rlm objects from the MASS package.
rq
An extract method for rq objects from the quantreg package.
sarlm
An extract method for sarlm objects from the spdep package.
sclm
An extract method for sclm objects from the ordinal package.
selection
An extract method for selection objects from the sampleSelection package.
sienaFit
An extract method for sienaFit objects from the RSiena package.
simex
An extract method for simex objects from the simex package.
stergm
An extract method for stergm objects from the tergm package.
survreg
An extract method for survreg objects from the survival package.
survreg.penal
An extract method for survreg.penal objects from the survival package.
svyglm
An extract method for svyglm objects from the survey package.
systemfit
An extract method for systemfit objects from the systemfit package.
texreg
An extract method for texreg objects from the texreg package. The purpose is to allow for easy manipulation of the output. texreg
objects can be created using the createTexreg function or using the extract function. After manipulating the object, it can be handed back to the screenreg, texreg, or htmlreg functions for creating a table.
tobit
An extract method for tobit objects from the AER package.
vglm
An extract method for vglm objects from the VGAM package.
weibreg
An extract method for weibreg objects from the eha package.
wls
An extract method for wls objects from the metaSEM package.
zelig
An extract method for zelig objects from the Zelig package.
Zelig
An extract method for Zelig objects from the Zelig package.
When fitting models, Zelig often wraps additional information around a model object produced by a different R
library. It is often possible to recover that model object using the from_zelig_model
function from Zelig (>= 5.0-16). If that underlying model is supported by texreg
, tables will be produced as usual, automatically. To identify the relevant model-specific arguments (e.g., include.adjrs = TRUE
), identify the class of the underlying model (class(Zelig::from_zelig_model(model))
), and check the appropriate extract.*
function in texreg
.
zeroinfl
An extract method for zeroinfl objects from the pscl package.
extract
is a generic function which extracts coefficients and GOF measures from statistical model objects. There are several extract methods for the specific model types, which 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.
Leifeld, Philip (2013). texreg: Conversion of Statistical Model Output in R to LaTeX and HTML Tables. Journal of Statistical Software, 55(8), 1-24. http://www.jstatsoft.org/v55/i08/.