texreg (version 1.36.18)

extract: Extract coefficients and GOF measures from a statistical object

Description

Extract coefficients and GOF measures from a statistical object.

Usage

extract(model, ...)
"extract"(model, include.loglik = TRUE,  include.lr = TRUE, include.nobs = TRUE, include.events = TRUE,  include.trisk = TRUE, ...)
"extract"(model, include.pvalues = FALSE,  include.aic = TRUE, include.loglik = TRUE, ...)
"extract"(model, include.pvalues = FALSE,  include.aic = TRUE, include.aicc = TRUE, include.bic = TRUE,  include.loglik = TRUE, ...)
"extract"(model, use.ci = FALSE,  adjusted.se = FALSE, include.nobs = TRUE, ...)
"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, ...)
"extract"(model, include.precision = TRUE,  include.pseudors = TRUE, include.loglik = TRUE,  include.nobs = TRUE, ...)
"extract"(model, include.aic = TRUE,  include.bic = TRUE, include.loglik = TRUE,  include.deviance = TRUE, include.nobs = TRUE, ...)
"extract"(model, level = 0.95,  include.nobs = TRUE, ...)
"extract"(model, include.aic = TRUE,  include.bic = TRUE, include.loglik = TRUE,  include.nobs = TRUE, ...)
"extract"(model, include.thresholds = TRUE,  include.aic = TRUE, include.bic=TRUE, include.loglik = TRUE,  include.nobs = TRUE, ...)
"extract"(model, include.thresholds = TRUE, include.loglik = TRUE, include.aic = TRUE,   include.bic = TRUE, include.nobs = TRUE,  include.groups = TRUE, include.variance = TRUE, ...)
"extract"(model, include.aic = TRUE,  include.rsquared = TRUE, include.maxrs = TRUE,  include.events = TRUE, include.nobs = TRUE,  include.missings = TRUE, ...)
"extract"(model, ...)
"extract"(model, include.aic = TRUE,  include.rsquared = TRUE, include.maxrs=TRUE,  include.events = TRUE, include.nobs = TRUE,  include.missings = TRUE, include.zph = TRUE, ...)
"extract"(model, include.aic = TRUE,  include.rsquared = TRUE, include.maxrs = TRUE,  include.events = TRUE, include.nobs = TRUE,  include.missings = TRUE, include.zph = TRUE, ...)
"extract"(model, include.rsquared = TRUE,  include.adjrs = TRUE, include.nobs = TRUE,  include.fstatistic = FALSE, include.rmse = TRUE, ...)
"extract"(model, include.aic = TRUE,  include.bic = TRUE, include.loglik = TRUE, ...)
"extract"(model, include.bic = TRUE, ...)
"extract"(model, include.pvalues = FALSE,  include.aic = TRUE, include.aicc = TRUE, include.bic = TRUE,  include.loglik = TRUE, ...)
"extract"(model, include.nobs = TRUE,  include.rsquared = TRUE, include.adjrs = TRUE,  include.fstatistic = FALSE, ...)
"extract"(model, include.nobs = TRUE,  include.aic = TRUE, include.loglik = TRUE, ...)
"extract"(model, ...)
"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, ...)
"extract"(model, robust = FALSE,  include.nobs = TRUE, include.nagelkerke = TRUE,  include.gaic = TRUE, ...)
"extract"(model, robust = TRUE,  include.dispersion = TRUE, include.nobs = TRUE, ...)
"extract"(model, include.scale = TRUE,  include.correlation = TRUE, include.nobs = TRUE, ...)
"extract"(model, include.obj.fcn = TRUE,  include.overidentification = FALSE, include.nobs = TRUE,  overIdentTest = c("LR", "LM", "J "), ...)
"extract"(model, include.aic = TRUE,  include.bic = TRUE, include.loglik = TRUE,  include.deviance = TRUE, include.nobs = TRUE, ...)
"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, ...)
"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, ...)
"extract"(model, include.aic = TRUE,  include.bic = TRUE, include.loglik = TRUE,  include.nobs = TRUE, include.groups = TRUE,  include.variance = FALSE, ...)
"extract"(model, include.nobs = TRUE, ...)
"extract"(model, include.aic = TRUE,  include.bic = TRUE, include.loglik = TRUE,  include.nobs = TRUE, ...)
"extract"(model, include.obj.fcn = TRUE,  include.overidentification = FALSE, include.nobs = TRUE, ...)
"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, ...)
"extract"(model, beside = FALSE,  include.count = TRUE, include.zero = TRUE, include.aic = TRUE,  include.loglik = TRUE, include.nobs = TRUE, ...)
"extract"(model, include.rsquared = TRUE,  include.adjrs = TRUE, include.nobs = TRUE,  include.fstatistic = FALSE, include.rmse = TRUE, ...)
"extract"(model, include.rsquared = TRUE,  include.adjrs = TRUE, include.nobs = TRUE,  include.fstatistic = FALSE, include.rmse = TRUE, ...)
"extract"(model, include.aic = TRUE,  include.bic = TRUE, include.loglik = TRUE,  include.nobs = TRUE, include.groups = TRUE,  include.variance = FALSE, ...)
"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, ...)
"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, ...)
"extract"(model, include.nobs = TRUE, ...)
"extract"(model, include.rsquared = TRUE,  include.adjrs = TRUE, include.aic = TRUE, include.bic = TRUE,  include.loglik = TRUE, ...)
"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, ...)
"extract"(model, include.pseudors = TRUE,  include.lr = TRUE, include.nobs = TRUE, ...)
"extract"(model, ...)
"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, ...)
"extract"(model, include.aic = TRUE,  include.loglik = TRUE, include.nobs = TRUE,  include.groups = TRUE, include.intercept = TRUE,  include.iterations = FALSE, beside = FALSE, ...)
"extract"(model, include.aic = TRUE,  include.loglik = TRUE, include.nobs = TRUE, ...)
"extract"(model, include.loglik = TRUE,  include.aicc = TRUE, include.delta = TRUE,  include.weight = TRUE, include.nobs = TRUE, ...)
"extract"(model, include.nobs = TRUE,  include.aic = TRUE, include.bic = TRUE, include.loglik = TRUE,  ...) 
"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, ...)
"extract"(model, include.aic = TRUE,  include.bic = TRUE, include.loglik = TRUE,  include.deviance = TRUE, include.nobs = TRUE, ...)
"extract"(model, include.aic = TRUE,  include.bic = TRUE, include.deviance = TRUE,  include.nobs = TRUE, ...)
"extract"(model, include.aic = TRUE,  include.bic = TRUE, include.loglik = TRUE,  include.nobs = TRUE, include.groups = TRUE,  include.variance = FALSE, ...)
"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, ...)
"extract"(model, include.nobs = TRUE,  include.rsquared = TRUE, include.adjrs = TRUE,  include.fstatistic = FALSE, include.lr = TRUE, ...)
"extract"(model, include.nobs = TRUE,  include.sargan = TRUE, include.wald = TRUE, ...)
"extract"(model, include.loglik = TRUE,  include.lr = TRUE, include.nobs = TRUE, include.events = TRUE,  include.trisk = TRUE, ...)
"extract"(model, include.rsquared = TRUE,  include.adjrs = TRUE, include.nobs = TRUE, ...)
"extract"(model, include.nobs = TRUE, ...)
"extract"(model, include.thresholds = FALSE,  include.aic = TRUE, include.bic = TRUE, include.loglik = TRUE,  include.deviance = TRUE, include.nobs = TRUE, ...)
"extract"(model, include.nvertices = TRUE,  include.events = TRUE, include.aic = TRUE,  include.aicc = TRUE, include.bic = TRUE, ...)
"extract"(model, include.nobs = TRUE, ...)
"extract"(model, include.nobs = TRUE,  include.percentile = TRUE, ...)
"extract"(model, include.nobs = TRUE,  include.loglik = TRUE, include.aic = TRUE, include.lr = TRUE,  include.wald = TRUE, ...)
"extract"(model, include.thresholds = TRUE,  include.aic = TRUE, include.bic = TRUE, include.loglik = TRUE,  include.nobs = TRUE, ...)
"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, ...)
"extract"(model, include.iterations = TRUE,  ...)
"extract"(model, jackknife = TRUE,  include.nobs = TRUE, ...)
"extract"(model, beside = FALSE,  include.formation = TRUE, include.dissolution = TRUE,  include.nvertices = TRUE, include.aic = FALSE,  include.bic = FALSE, include.loglik = FALSE, ...)
"extract"(model, include.aic = TRUE,  include.bic = TRUE, include.loglik = TRUE,  include.deviance = TRUE, include.nobs = TRUE, ...)
"extract"(model, include.aic = TRUE,  include.bic = TRUE, include.loglik = TRUE,  include.deviance = TRUE, include.nobs = TRUE, ...)
"extract"(model, include.aic = FALSE,  include.bic = FALSE, include.loglik = FALSE,  include.deviance = TRUE, include.dispersion = TRUE,  include.nobs = TRUE, ...)
"extract"(model, include.rsquared = TRUE,  include.adjrs = TRUE, include.nobs = TRUE, beside = FALSE,  include.suffix = FALSE, ...)
"extract"(model, ...)
"extract"(model, include.aic = TRUE,  include.bic = TRUE, include.loglik = TRUE,  include.deviance = TRUE, include.nobs = FALSE,  include.censnobs = TRUE, include.wald=TRUE, ...)
"extract"(model, include.loglik = TRUE,  include.lr = TRUE, include.nobs = TRUE,  include.events = TRUE, include.trisk = TRUE, ...)
"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, ...)
"extract"(model, include.aic = TRUE,  include.bic = TRUE, include.loglik = TRUE,  include.deviance = TRUE, include.nobs = TRUE,  include.censnobs = TRUE, include.wald = TRUE, ...)
"extract"(model, beside = FALSE,  include.count = TRUE, include.zero = TRUE, include.aic = TRUE,  include.loglik = TRUE, include.nobs = TRUE, ...)

Arguments

model

A statistical model object.

adjusted.se

If available: use adjusted rather than default standard errors?

beside

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.

include.adjrs

If available: should the adjusted R-squared be reported?

include.aic

If available: should Akaike's information criterion (AIC) be reported?

include.aicc

If available: should AICc be reported? This is a version of AIC with a correction for finite sample sizes.

include.auc

If available: should the area under the curve (AUC) be reported?

include.bic

If available: should the Bayesian information criterion (BIC) be reported?

include.censnobs

If available: should the total, right-censored, left-censored, and uncensored number of observations be reported?

include.correlation

If available: should the correlation parameter alpha and its standard error be reported (for geeglm models)?

include.count

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)?

include.delta

If available: should the delta statistic be included?

include.dev.expl

If available: should the deviance explained be reported?

include.deviance

If available: should the deviance be reported?

include.dic

If available: should the deviance information criterion (DIC) be reported?

include.dispersion

If available: should the dispersion or scale parameter be reported?

include.dissolution

If available: should the coefficients for the dissolution phase in a STERGM be reported?

include.errors

If available: should the error terms of a sample selection model be reported?

include.events

If available: should the number of events be reported (in survival models)?

include.formation

If available: should the coefficients for the formation phase in a STERGM be reported?

include.fstatistic

If available: should the F statistic be reported?

include.gaic

If available: should the Generalized Akaike's information criterion (GAIC) be reported?

include.gini

If available: should the Gini coefficient be reported?

include.gcv

If available: should the GCV score be reported (in GAMs)?

include.groups

If available: should the number of groups in a mixed-effects model (or k alternatives in a multinomial choice model) be reported?

include.intercept

If available: should the intercept be included in the GOF block?

include.iterations

If available: should the number of iterations be included?

include.loglik

If available: should the log-likelihood be reported?

include.logloss

If available: should the log loss be reported?

include.lr

If available: should the likelihood ratio test be reported?

include.maxrs

If available: should the maximum possible R-squared be reported?

include.meanerror

If available: should the mean per-class error be reported?

include.missings

If available: should the number of missing observations be reported (in survival models)?

include.mse

If available: should the mean square error be reported?

include.nagelkerke

If available: should Nagelkerke's R-squared be reported?

include.nobs

If available: should the number of observations be reported?

include.nsmooth

If available: should the number of smooth terms be reported (in GAMs)?

include.nvertices

If available: should the number of vertices be reported in a statistical network model?

include.obj.fcn

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).

include.outcome

If available: should the outcome component of a sample selection model be reported?

include.overidentification

If available: should the J-test for overidentification be reported (for gel and gmm objects)?

include.percentile

If available: should the percentile (tau) be reported?

include.precision

If available: should the precision estimates of a betareg fit (the phi coefficients) be reported as part of the coefficients block?

include.pseudors

If available: should the pseudo R-squared be reported?

include.pvalues

If available: should the p values be reported (naive p values are not recommended for lme4 models, but see also the mcmc.pvalues argument)?

include.rmse

If available: should the root-mean-square error (= residual standard deviation) be reported?

include.rsquared

If available: should R-squared be reported?

include.sargan

If available: should the Sargan test be reported?

include.scale

If available: should the scale parameter gamma and its standard error be reported (for geeglm models)?

include.selection

If available: should the selection component of a sample selection model be reported?

include.smooth

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).

include.suffix

If available: include the name of the current model in parentheses after each model term (instead of before the model term).

include.tau

If available: include tau in linear quantile mixed models?

include.thresholds

If available: should the threshold parameters (that is, the intercepts for the class boundaries) be reported in ordinal models?

include.trisk

If available: should the total time at risk be reported (in event-history models)?

include.variance

If available: should group variances be reported?

include.wald

If available: should the Wald statistic be included?

include.weight

If available: should the weight be included?

include.zero

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)?

include.zph

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)?

jackknife

If available: use Jackknife variance instead of Asymptotic variance.

level

Confidence level (1 - alpha) for computing confidence intervals.

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.

method

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.

nsim

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.

overIdentTest

If available: which test statistics should be included in an overidentification test (for gel and gmm objects)?

prefix

Include prefix before the label of the coefficient in order to identify the current model component.

robust

If available: report robust instead of naive standard errors.

standardized

If available: report standardized coefficients instead of raw coefficients?

use.ci

Use confidence intervals rather than standard errors.

...

Custom parameters which are handed over to subroutines.

Methods

Details

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.

References

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/.

See Also

texreg-package texreg