A numeric object to reformat.

Should a leading zero be printed if the coefficient is non-negative and smaller than one (e.g., "0.23" as opposed to ".23")?

Number of decimal places to round to.

A character vector representing a column in a regression table.

Should the width left of the separator/bracket be calculated? If FALSE, the width right of the separator/bracket is computed.

Was the single.row argument used to construct the regression table? I.e., are both the coefficient and uncertainty measure (SE or CI) in the same rows of the matrix?

The separator symbol to match. These can be closing parentheses (in the case of standard errors when single.row is switched on), closing square brackets (in the case of confidence intervals), or dots (in the case of single.row = FALSE, for decimal alignment at the actual decimal separator).

The names for the covariates in a model as a character vector (= row names).

The coefficients as a numeric vector. Can have length zero.

The standard errors as a numeric vector. Can have length zero.

The p-values as a numeric vector. Can have length zero.

The lower bounds of the confidence intervals as a numeric vector. Can have length zero.

The upper bounds of the confidence intervals as a numeric vector. Can have length zero.

Names of the goodness-of-fit statistics as a character vector. Can have length zero.

Goodness-of-fit statistics as a numeric vector. Can have length zero.

A logical vector with as many elements as the gof argument, indicating whether the respective GOF statistic is a double (TRUE) or integer (FALSE) number or whether it is a character entry (NA).

A name for the statistical model. Can be a character vector of length zero if there is no model name.

A character vector of original model names, before any custom columns are inserted.

The same argument as specified in the link{matrixreg} function.

The same argument as specified in the link{matrixreg} function.

Return the column types? If FALSE, the column names in the possible presence of custom columns are returned.

A statistical model object.

Custom parameters, which are handed over to subroutines. The arguments are usually passed to the summary function, but in some cases to other functions.

A statistical model object.

Custom parameters, which are handed over to subroutines. Currently not in use.

A statistical model object.

Report p-values?

Report Akaike's Information Criterion (AIC) in the GOF block?

Report the Bayesian Information Criterion (BIC) in the GOF block?

Report the log likelihood in the GOF block?

Report the number of observations in the GOF block?

Custom parameters, which are handed over to subroutines. Currently not in use.

A statistical model object.

Report standardized coefficients instead of raw coefficients?

Report the mean squared error in the GOF block?

Report R^2 in the GOF block?

Report the log loss?

Report the mean per-class error?

Report the area under the curve (AUC)?

Report the Gini coefficient?

Report the deviance?

Report Akaike's Information Criterion (AIC) in the GOF block?

Custom parameters, which are handed over to subroutines. Currently not in use.

A statistical model object.

Report the number of observations in the GOF block?

Report the log likelihood in the GOF block?

Report Akaike's Information Criterion (AIC) in the GOF block?

Report likelihood ratio test?

Report the Wald statistic?

Custom parameters, which are handed over to subroutines, in this case to the summary method for the object.

A statistical model object.

Report Akaike's Information Criterion (AIC) in the GOF block?

Report the log likelihood in the GOF block?

Report likelihood ratio test?

Report the number of observations in the GOF block?

Report the number of events in the GOF block?

Report the total time at risk (in event-history models)?

Custom parameters, which are handed over to subroutines. Currently not in use.

A statistical model object.

Report confidence intervals in the GOF block?

Report adjusted standard error in the GOF block?

Report the number of observations in the GOF block?

Custom parameters, which are handed over to subroutines. Currently not in use.

A statistical model object.

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).

Report Akaike's Information Criterion (AIC) in the GOF block?

Report the Bayesian Information Criterion (BIC) in the GOF block?

Report the log likelihood in the GOF block?

Report the deviance?

Report the deviance explained?

Report the dispersion parameter?

Report R^2 in the GOF block?

Report the GCV score?

Report the number of observations in the GOF block?

Report the number of smooth terms?

Custom parameters, which are handed over to subroutines, in this case to the summary method for the object.

A statistical model object.

Report the posterior median instead of the default posterior mean as coefficients?

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.

A statistical model object.

Report pseudo R^2 in the GOF block?

Report the log likelihood in the GOF block?

Report the number of observations in the GOF block?

Custom parameters, which are handed over to subroutines. Currently not in use.

A statistical model object.

Report pseudo R^2 in the GOF block?

Report the log likelihood in the GOF block?

Report the number of observations in the GOF block?

Custom parameters, which are handed over to subroutines. Currently not in use.

A statistical model object.

Report precision in the GOF block?

Report pseudo R^2 in the GOF block?

Report the log likelihood in the GOF block?

Report the number of observations in the GOF block?

Custom parameters, which are handed over to subroutines, in this case to the summary method for the object.

A statistical model object.

Report the log likelihood in the GOF block?

Report the residual deviance?

Report the number of observations in the GOF block?

Custom parameters, which are handed over to subroutines. Currently not in use.

A statistical model object.

Report the number of observations in the GOF block?

Report Akaike's Information Criterion (AIC) in the GOF block?

Report confidence intervals in the GOF block?

Custom parameters, which are handed over to subroutines. Currently not in use.

A statistical model object.

Report Akaike's Information Criterion (AIC) in the GOF block?

Report the Bayesian Information Criterion (BIC) in the GOF block?

Report the log likelihood in the GOF block?

Report the deviance?

Report the number of observations in the GOF block?

Custom parameters, which are handed over to subroutines, in this case to the summary method for the object.

A statistical model object.

Report highest posterior density (HPD) intervals (HDI) using the HPDinterval function in the coda package, with the probability given in the level argument, instead of the default 95 percent posterior quantiles?

Significance level (1 - alpha) for HPDs (in combination with the use.HDI argument).

Include random effects (standard deviations) in the GOF block of the table?

Report R^2 in the GOF block?

Report the number of observations in the GOF block?

Report Leave-One-Out Information Criterion?

Recompute exact cross-validation for problematic observations for which approximate leave-one-out cross-validation may return incorrect results? This is done using the reloo.brmsfit function and may take some time to compute.

Report Widely Applicable Information Criterion (WAIC)?

Custom parameters, which are handed over to subroutines, in this case to the summary method for the object.

A statistical model object.

Significance or confidence level (1 - alpha) for computing confidence intervals.

Report the number of observations in the GOF block?

Custom parameters, which are handed over to subroutines. Currently not in use.

A statistical model object.

Report Akaike's Information Criterion (AIC) in the GOF block?

Report the Bayesian Information Criterion (BIC) in the GOF block?

Report the log likelihood in the GOF block?

Report the number of observations in the GOF block?

Custom parameters, which are handed over to subroutines, in this case to the summary method for the object.

A statistical model object.

Report thresholds in the GOF block?

Report Akaike's Information Criterion (AIC) in the GOF block?

Report the Bayesian Information Criterion (BIC) in the GOF block?

Report the log likelihood in the GOF block?

Report the number of observations in the GOF block?

Custom parameters, which are handed over to subroutines, in this case to the summary method for the object.

A statistical model object.

Report thresholds in the GOF block?

Report the log likelihood in the GOF block?

Report Akaike's Information Criterion (AIC) in the GOF block?

Report the Bayesian Information Criterion (BIC) in the GOF block?

Report the number of observations in the GOF block?

Report the number of groups?

Report group variances?

Custom parameters, which are handed over to subroutines, in this case to the summary method for the object.

A statistical model object.

Report Akaike's Information Criterion (AIC) in the GOF block?

Report R^2 in the GOF block?

Report maximal R^2 in the GOF block?

Report the number of events in the GOF block?

Report the number of observations in the GOF block?

Report number of missing data points in the GOF block?

Custom parameters, which are handed over to subroutines, in this case to the summary method for the object.

A statistical model object.

Custom parameters, which are handed over to subroutines. Currently not in use.

A statistical model object.

Report Akaike's Information Criterion (AIC) in the GOF block?

Report R^2 in the GOF block?

Report maximal R^2 in the GOF block?

Report the number of events in the GOF block?

Report the number of observations in the GOF block?

Report number of missing data points in the GOF block?

Report proportional hazard test in the GOF block?

Custom parameters, which are handed over to subroutines, in this case to the summary method for the object.

A statistical model object.

Report Akaike's Information Criterion (AIC) in the GOF block?

Report R^2 in the GOF block?

Report maximal R^2 in the GOF block?

Report the number of events in the GOF block?

Report the number of observations in the GOF block?

Report number of missing data points in the GOF block?

Report proportional hazard test in the GOF block?

Custom parameters, which are handed over to subroutines, in this case to the summary method for the object.

A statistical model object.

Report Akaike's Information Criterion (AIC) in the GOF block?

Report the log likelihood in the GOF block?

Report likelihood ratio test?

Report the number of observations in the GOF block?

Report the number of events in the GOF block?

Report the total time at risk (in event-history models)?

Custom parameters, which are handed over to subroutines. Currently not in use.

A statistical model object.

Report R^2 in the GOF block?

Report adjusted R^2 in the GOF block?

Report the number of observations in the GOF block?

Report the F-statistic in the GOF block?

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 summary method for the object.

A statistical model object.

Report Akaike's Information Criterion (AIC) in the GOF block?

Report the Bayesian Information Criterion (BIC) in the GOF block?

Report the log likelihood in the GOF block?

Custom parameters, which are handed over to subroutines, in this case to the summary method for the object.

A statistical model object.

Report the Bayesian Information Criterion (BIC) in the GOF block?

Custom parameters, which are handed over to subroutines. Currently not in use.

A statistical model object.

Report p-values?

Report Akaike's Information Criterion (AIC) in the GOF block?

Report AICC in the GOF block?

Report the Bayesian Information Criterion (BIC) in the GOF block?

Report the log likelihood in the GOF block?

Custom parameters, which are handed over to subroutines. Currently not in use.

A statistical model object.

Report the number of observations in the GOF block?

Report Akaike's Information Criterion (AIC) in the GOF block?

Report the log likelihood in the GOF block?

Custom parameters, which are handed over to subroutines. Currently not in use.

A statistical model object.

Report the deviance?

Report the number of observations in the GOF block?

Report the number of groups?

Custom parameters, which are handed over to subroutines, in this case to the summary method for the object.

A statistical model object.

Report R^2 in the GOF block?

Report adjusted R^2 in the GOF block?

Report the number of observations in the GOF block?

Report the number of groups?

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 summary method for the object.

A statistical model object.

Report the number of observations in the GOF block?

Report R^2 in the GOF block?

Report adjusted R^2 in the GOF block?

Report the F-statistic in the GOF block?

Include statistics for projected model in the GOF block?

Report the number of groups?

Custom parameters, which are handed over to subroutines, in this case to the summary method for the object.

A statistical model object.

Report the number of observations?

Report the number of groups?

Report R^2? (OLS only)

Report adjusted R^2? (OLS only)

Include statistics for projected model? (OLS only)

Report the deviance? (GLM/MLE only)

Report the log likelihood? (GLM/MLE only)

Report Pseudo-R^2? (GLM/MLE only)

Custom parameters, which are handed over to the coeftable method for the fixest object.

A statistical model object.

Custom parameters, which are handed over to subroutines. Currently not in use.

A statistical model object.

Report p-values?

Report Akaike's Information Criterion (AIC) in the GOF block?

Report AICC in the GOF block?

Report the Bayesian Information Criterion (BIC) in the GOF block?

Report the log likelihood in the GOF block?

Report the number of observations in the GOF block?

Custom parameters, which are handed over to subroutines. Currently not in use.

A statistical model object.

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).

Report Akaike's Information Criterion (AIC) in the GOF block?

Report the Bayesian Information Criterion (BIC) in the GOF block?

Report the log likelihood in the GOF block?

Report the deviance?

Report the deviance explained?

Report the dispersion parameter?

Report R^2 in the GOF block?

Report the GCV score?

Report the number of observations in the GOF block?

Report the number of smooth terms?

Custom parameters, which are handed over to subroutines, in this case to the summary method for the object.

A statistical model object.

If TRUE computes robust standard errors in the variance-covariance matrix.

Report the number of observations in the GOF block?

Report Nagelkerke R^2 in the GOF block?

Report Generalized Akaike's Information Criterion (AIC) in the GOF block?

Custom parameters, which are handed over to subroutines, in this case to the vcov method for the object.

A statistical model object.

The type.

Report the number of observations in the GOF block?

Report Generalized Akaike's Information Criterion (AIC) in the GOF block?

Custom parameters, which are handed over to subroutines, in this case to the vcov method for the object.

A statistical model object.

If TRUE computes robust standard errors in the variance-covariance matrix.

Report the dispersion or scale parameter?

Report the number of observations in the GOF block?

Custom parameters, which are handed over to subroutines, in this case to the summary method for the object.

A statistical model object.

Report the dispersion or scale parameter?

Report the correlation parameter alpha and its standard error?

Report the number of observations in the GOF block?

Custom parameters, which are handed over to subroutines. Currently not in use.

A statistical model object.

Report the value of the objective function (= criterion function)? More precisely, this returns E(g)var(g)^{-1}E(g).

Report the J-test for overidentification?

Report the number of observations in the GOF block?

Which test statistics should be included in an overidentification test?

Custom parameters, which are handed over to subroutines, in this case to the summary method for the object.

A statistical model object.

Report Akaike's Information Criterion (AIC) in the GOF block?

Report the Bayesian Information Criterion (BIC) in the GOF block?

Report the log likelihood in the GOF block?

Report the deviance?

Report the number of observations in the GOF block?

Custom parameters, which are handed over to subroutines, in this case to the summary method for the object.

A statistical model object.

Report Akaike's Information Criterion (AIC) in the GOF block?

Report the Bayesian Information Criterion (BIC) in the GOF block?

Report the log likelihood in the GOF block?

Report the deviance?

Report the number of observations in the GOF block?

Custom parameters, which are handed over to subroutines. Currently not in use.

A statistical model object.

The method used to compute confidence intervals or p-values. The default value "naive" computes naive p-values while the other methods compute confidence intervals using the confint function. See confint.merMod.

Significance or confidence level (1 - alpha) for computing confidence intervals.

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.

Report Akaike's Information Criterion (AIC) in the GOF block?

Report the Bayesian Information Criterion (BIC) in the GOF block?

Report the deviance information criterion (DIC)?

Report the deviance?

Report the log likelihood in the GOF block?

Report the number of observations in the GOF block?

Report the number of groups?

Report group variances?

Arguments to be passed to the fixef function in the lme4 package.

A statistical model object.

Report Akaike's Information Criterion (AIC) in the GOF block?

Report the Bayesian Information Criterion (BIC) in the GOF block?

Report the log likelihood in the GOF block?

Report the number of observations in the GOF block?

Report the number of groups?

Report group variances?

Custom parameters, which are handed over to subroutines, in this case to the summary method for the object.

A statistical model object.

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.

Report the count parameters in the coefficients block (before the binary part for the zeros)?

Should the binary part of the model be included in the coefficients block (after the count parameters)?

Report Akaike's Information Criterion (AIC) in the GOF block?

Report the number of groups?

Report group variances?

Report the log likelihood in the GOF block?

Report the number of observations in the GOF block?

Custom parameters, which are handed over to subroutines, in this case to the summary method for the object.

A statistical model object.

Report group variances?

Report the dispersion parameter?

Should the binary part of a zero-inflated regression model or hurdle model be included in the coefficients block (after the count model)?

Report Akaike's Information Criterion (AIC) in the GOF block?

Report the Bayesian Information Criterion (BIC) in the GOF block?

Report the log likelihood in the GOF block?

Report the number of observations in the GOF block?

Report the number of groups?

Custom parameters, which are handed over to subroutines. Currently not in use.

A statistical model object.

Report the number of observations in the GOF block?

Custom parameters, which are handed over to subroutines, in this case to the summary method for the object.

A statistical model object.

Report Akaike's Information Criterion (AIC) in the GOF block?

Report the Bayesian Information Criterion (BIC) in the GOF block?

Report the log likelihood in the GOF block?

Report the number of observations in the GOF block?

Custom parameters, which are handed over to subroutines, in this case to the summary method for the object.

A statistical model object.

Report the value of the objective function (= criterion function)? More precisely, this returns E(g)var(g)^{-1}E(g).

Report the J-test for overidentification?

Report the number of observations in the GOF block?

Custom parameters, which are handed over to subroutines, in this case to the summary method for the object.

A statistical model object.

Report Akaike's Information Criterion (AIC) in the GOF block?

Report the Bayesian Information Criterion (BIC) in the GOF block?

Report the log likelihood in the GOF block?

Report the number of observations in the GOF block?

Custom parameters, which are handed over to subroutines, in this case to the summary method for the object.

A statistical model object.

Report Akaike's Information Criterion (AIC) in the GOF block?

Report the Bayesian Information Criterion (BIC) in the GOF block?

Report the log likelihood in the GOF block?

Report the deviance?

Report the number of observations in the GOF block?

Report the degrees of freedom?

Report the chi squared statistic?

Report the delta statistic?

Custom parameters, which are handed over to subroutines. Currently not in use.

A statistical model object.

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.

Report the count parameters in the coefficients block (before the binary part for the zeros)?

Should the binary part of the model be included in the coefficients block (after the count parameters)?

Report Akaike's Information Criterion (AIC) in the GOF block?

Report the log likelihood in the GOF block?

Report the number of observations in the GOF block?

Custom parameters, which are handed over to subroutines, in this case to the summary method for the object.

A statistical model object.

Report R^2 in the GOF block?

Report adjusted R^2 in the GOF block?

Report the number of observations in the GOF block?

Report the F-statistic in the GOF block?

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 summary method for the object.

A statistical model object.

Report R^2 in the GOF block?

Report adjusted R^2 in the GOF block?

Report the number of observations in the GOF block?

Report the F-statistic in the GOF block?

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 summary method for the object.

A statistical model object.

Report R^2 in the GOF block?

Report adjusted R^2 in the GOF block?

Report the number of observations in the GOF block?

Report the F-statistic in the GOF block?

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.

A statistical model object.

Report Akaike's Information Criterion (AIC) in the GOF block?

Report the Bayesian Information Criterion (BIC) in the GOF block?

Report the log likelihood in the GOF block?

Report the number of observations in the GOF block?

Report the number of groups?

Report group variances?

Custom parameters, which are handed over to subroutines, in this case to the summary method for the object.

A statistical model object.

The method used to compute confidence intervals or p-values. The default value "naive" computes naive p-values while the other methods compute confidence intervals using the confint function. See confint.merMod.

Significance or confidence level (1 - alpha) for computing confidence intervals.

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.

Report Akaike's Information Criterion (AIC) in the GOF block?

Report the Bayesian Information Criterion (BIC) in the GOF block?

Report the deviance information criterion (DIC)?

Report the deviance?

Report the log likelihood in the GOF block?

Report the number of observations in the GOF block?

Report the number of groups?

Report group variances?

Arguments to be passed to the fixef function in the lme4 package.

A statistical model object.

The method used to compute confidence intervals or p-values. The default value "naive" computes naive p-values while the other methods compute confidence intervals using the confint function. See confint.merMod.

Significance or confidence level (1 - alpha) for computing confidence intervals.

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.

Report Akaike's Information Criterion (AIC) in the GOF block?

Report the Bayesian Information Criterion (BIC) in the GOF block?

Report the deviance information criterion (DIC)?

Report the deviance?

Report the log likelihood in the GOF block?

Report the number of observations in the GOF block?

Report the number of groups?

Report group variances?

Arguments to be passed to the fixef function in the lme4 package.

A statistical model object.

Report the number of observations in the GOF block?

Custom parameters, which are handed over to subroutines, in this case to the summary method for the object.

Report R^2 in the GOF block?

Report the root mean square error (RMSE; = residual standard deviation) in the GOF block?

A statistical model object.

Report R^2 in the GOF block?

Report adjusted R^2 in the GOF block?

Report Akaike's Information Criterion (AIC) in the GOF block?

Report the Bayesian Information Criterion (BIC) in the GOF block?

Report the log likelihood in the GOF block?

Custom parameters, which are handed over to subroutines, in this case to the coef method for the object.

A statistical model object.

Report the number of observations in the GOF block?

Report the log likelihood in the GOF block?

Report the deviance?

Report Akaike's Information Criterion (AIC) in the GOF block?

Report the Bayesian Information Criterion (BIC) in the GOF block?

Custom parameters, which are handed over to subroutines. Currently not in use.

A statistical model object.

Report the number of observations in the GOF block?

Report the log likelihood in the GOF block?

Report the deviance?

Report Akaike's Information Criterion (AIC) in the GOF block?

Report the Bayesian Information Criterion (BIC) in the GOF block?

Custom parameters, which are handed over to subroutines. Currently not in use.

A statistical model object.

Include the number of observations in summary table?

Include the log-likelihood in summary table?

Include the the AIC in summary table?

Include the the BIC in summary table?

Custom parameters, which are handed over to subroutines. Currently not in use.

A statistical model object.

Report Akaike's Information Criterion (AIC) in the GOF block?

Report the Bayesian Information Criterion (BIC) in the GOF block?

Report the log likelihood in the GOF block?

Report the number of observations in the GOF block?

Report the number of groups?

Report tau?

Report confidence intervals in the GOF block?

Arrange the model terms below each other or beside each other?

Custom parameters, which are handed over to subroutines, in this case to the summary method for the object.

A statistical model object.

Report pseudo R^2 in the GOF block?

Report likelihood ratio test?

Report the number of observations in the GOF block?

Custom parameters, which are handed over to subroutines. Currently not in use.

A statistical model object.

Report the log likelihood in the GOF block?

Report the AIC in the GOF block?

Custom parameters, which are handed over to subroutines, in this case to the summary method for the object.

A statistical model object.

The method used to compute confidence intervals or p-values. The default value "naive" computes naive p-values while the other methods compute confidence intervals using the confint function. See confint.merMod.

Significance or confidence level (1 - alpha) for computing confidence intervals.

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.

Report Akaike's Information Criterion (AIC) in the GOF block?

Report the Bayesian Information Criterion (BIC) in the GOF block?

Report the deviance information criterion (DIC)?

Report the deviance?

Report the log likelihood in the GOF block?

Report the number of observations in the GOF block?

Report the number of groups?

Report group variances?

Arguments to be passed to the fixef function in the lme4 package.

A statistical model object.

Report the number of observations in the GOF block?

Report the log likelihood in the GOF block?

Custom parameters, which are handed over to subroutines, in this case to the summary method for the object.

A statistical model object.

Report Akaike's Information Criterion (AIC) in the GOF block?

Report the log likelihood in the GOF block?

Report the number of observations in the GOF block?

Report the number of groups?

Report coefficient names in alphabetical order?

Report the number of iterations?

Arrange the model terms below each other or beside each other?

Custom parameters, which are handed over to subroutines, in this case to the summary method for the object.

A statistical model object.

Report the log likelihood in the GOF block?

Report AICC in the GOF block?

Report the delta statistic?

Report Akaike weights?

Report the number of observations in the GOF block?

Custom parameters, which are handed over to subroutines. Currently not in use.

A statistical model object.

Report the number of observations in the GOF block?

Report Akaike's Information Criterion (AIC) in the GOF block?

Report the Bayesian Information Criterion (BIC) in the GOF block?

Report the log likelihood in the GOF block?

Custom parameters, which are handed over to subroutines. Currently not in use.

A statistical model object.

Report p-values?

Report Akaike's Information Criterion (AIC) in the GOF block?

Report the Bayesian Information Criterion (BIC) in the GOF block?

Report the log likelihood in the GOF block?

Report the deviance?

Report the number of observations in the GOF block?

Report the number of groups?

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.

Arrange the model terms below each other or beside each other?

Custom parameters, which are handed over to subroutines, in this case to the summary method for the object.

A statistical model object.

Report Akaike's Information Criterion (AIC) in the GOF block?

Report the Bayesian Information Criterion (BIC) in the GOF block?

Report the log likelihood in the GOF block?

Report the deviance?

Report the number of observations in the GOF block?

Custom parameters, which are handed over to subroutines, in this case to the summary method for the object.

A statistical model object.

Report the number of observations in the GOF block?

Report the log likelihood in the GOF block?

Report the deviance?

Report Akaike's Information Criterion (AIC) in the GOF block?

Report the Bayesian Information Criterion (BIC) in the GOF block?

Custom parameters, which are handed over to subroutines. Currently not in use.

A statistical model object.

Report the number of observations in the GOF block?

Report the log likelihood in the GOF block?

Report the deviance?

Report Akaike's Information Criterion (AIC) in the GOF block?

Report the Bayesian Information Criterion (BIC) in the GOF block?

Custom parameters, which are handed over to subroutines. Currently not in use.

A statistical model object.

Report Akaike's Information Criterion (AIC) in the GOF block?

Report the Bayesian Information Criterion (BIC) in the GOF block?

Report the deviance?

Report the number of observations in the GOF block?

Custom parameters, which are handed over to subroutines. Currently not in use.

A statistical model object.

Report Akaike's Information Criterion (AIC) in the GOF block?

Report the Bayesian Information Criterion (BIC) in the GOF block?

Report the log likelihood in the GOF block?

Report the number of observations in the GOF block?

Report the number of groups?

Report group variances?

Custom parameters, which are handed over to subroutines, in this case to the summary method for the object.

A statistical model object.

The method used to compute confidence intervals or p-values. The default value "naive" computes naive p-values while the other methods compute confidence intervals using the confint function. See confint.merMod.

Significance or confidence level (1 - alpha) for computing confidence intervals.

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.

Report Akaike's Information Criterion (AIC) in the GOF block?

Report the Bayesian Information Criterion (BIC) in the GOF block?

Report the deviance information criterion (DIC)?

Report the deviance?

Report the log likelihood in the GOF block?

Report the number of observations in the GOF block?

Report the number of groups?

Report group variances?

Arguments to be passed to the fixef function in the lme4 package.

A statistical model object.

Report Akaike's Information Criterion (AIC) in the GOF block?

Report the number of iterations?

Report the log likelihood in the GOF block?

Report the number of observations in the GOF block?

Report R^2 in the GOF block?

Custom parameters, which are handed over to subroutines, in this case to the summary method for the object.

A statistical model object.

Report the number of observations in the GOF block?

Report R^2 in the GOF block?

Report adjusted R^2 in the GOF block?

Report the F-statistic in the GOF block?

Report likelihood ratio test?

Custom parameters, which are handed over to subroutines. Currently not in use.

A statistical model object.

Report the HPY R-squared statistic in the GOF block?

Report the total and residual sum of squares in the GOF block?

Report the number of observations in the GOF block?

Custom parameters, which are handed over to subroutines, in this case to the summary method for the object.

A statistical model object.

Report Akaike's Information Criterion (AIC) in the GOF block?

Report the log likelihood in the GOF block?

Report the number of observations in the GOF block?

Custom parameters, which are handed over to subroutines, in this case to the summary method for the object.

A statistical model object.

Report the number of observations in the GOF block?

Report the Sargan test?

Report the Wald statistic?

Custom parameters, which are handed over to subroutines, in this case to the summary method for the object.

A statistical model object.

Report Akaike's Information Criterion (AIC) in the GOF block?

Report the log likelihood in the GOF block?

Report likelihood ratio test?

Report the number of observations in the GOF block?

Report the number of events in the GOF block?

Report the total time at risk (in event-history models)?

Custom parameters, which are handed over to subroutines. Currently not in use.

A statistical model object.

Report R^2 in the GOF block?

Report adjusted R^2 in the GOF block?

Report the number of observations in the GOF block?

Report group variances?

Custom parameters, which are handed over to subroutines, in this case to the summary method for the object.

A statistical model object.

Report the number of observations in the GOF block?

Custom parameters, which are handed over to subroutines, in this case to the summary method for the object.

A statistical model object.

Report the number of observations in the GOF block?

Report the log likelihood in the GOF block?

Report the deviance?

Report Akaike's Information Criterion (AIC) in the GOF block?

Report the Bayesian Information Criterion (BIC) in the GOF block?

Custom parameters, which are handed over to subroutines. Currently not in use.

A statistical model object.

Report the number of observations in the GOF block?

Report the log likelihood in the GOF block?

Report the deviance?

Report Akaike's Information Criterion (AIC) in the GOF block?

Report the Bayesian Information Criterion (BIC) in the GOF block?

Custom parameters, which are handed over to subroutines. Currently not in use.

A statistical model object.

Report thresholds in the GOF block?

Report Akaike's Information Criterion (AIC) in the GOF block?

Report the Bayesian Information Criterion (BIC) in the GOF block?

Report the log likelihood in the GOF block?

Report the deviance?

Report the number of observations in the GOF block?

Custom parameters, which are handed over to subroutines, in this case to the summary method for the object.

A statistical model object.

Report the number of observations in the GOF block?

Report the log likelihood in the GOF block?

Report the deviance?

Report Akaike's Information Criterion (AIC) in the GOF block?

Report the Bayesian Information Criterion (BIC) in the GOF block?

Custom parameters, which are handed over to subroutines. Currently not in use.

A statistical model object.

Report the number of vertices in a STERGM?

Report the number of events in the GOF block?

Report Akaike's Information Criterion (AIC) in the GOF block?

Report AICC in the GOF block?

Report the Bayesian Information Criterion (BIC) in the GOF block?

Custom parameters, which are handed over to subroutines. Currently not in use.

A statistical model object.

Report the number of observations in the GOF block?

Report Akaike's Information Criterion (AIC) in the GOF block?

Report Corrected Akaike's Information Criterion (AICc) in the GOF block?

Report the Bayesian Information Criterion (BIC) in the GOF block?

Report the log likelihood in the GOF block?

Report the posterior means, rather than the posterior modes, as coefficients?

Custom parameters, which are handed over to subroutines. Currently not in use.

A statistical model object.

Report the number of observations in the GOF block?

Custom parameters, which are handed over to subroutines, in this case to the summary method for the object.

A statistical model object.

Report the number of observations in the GOF block?

Report the percentile (tau)?

Custom parameters, which are handed over to subroutines, in this case to the summary method for the object.

A statistical model object.

Report thresholds in the GOF block?

Report Akaike's Information Criterion (AIC) in the GOF block?

Report the Bayesian Information Criterion (BIC) in the GOF block?

Report the log likelihood in the GOF block?

Report the number of observations in the GOF block?

Custom parameters, which are handed over to subroutines, in this case to the summary method for the object.

A statistical model object.

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

Report the selection component of a sample selection model?

Report the outcome component of a sample selection model?

Report the error terms of a sample selection model?

Report Akaike's Information Criterion (AIC) in the GOF

Report the Bayesian Information Criterion (BIC) in the GOF block?

Report the log likelihood in the GOF block?

Report R^2 in the GOF block?

Report adjusted R^2 in the GOF block?

Report the number of observations in the GOF block? block?

Custom parameters, which are handed over to subroutines, in this case to the summary method for the object.

A statistical model object.

Report the number of iterations?

Custom parameters, which are handed over to subroutines, in this case to the summary method for the object.

A statistical model object.

Use Jackknife variance instead of asymptotic variance?

Report the number of observations in the GOF block?

Custom parameters, which are handed over to subroutines, in this case to the summary method for the object.

A statistical model object.

Report Akaike's Information Criterion (AIC) in the GOF block?

Report the Bayesian Information Criterion (BIC) in the GOF block?

Report the log likelihood in the GOF block?

Report the deviance?

Report the number of observations in the GOF block?

Custom parameters, which are handed over to subroutines, in this case to the summary method for the object.

A statistical model object.

Report R^2 in the GOF block?

Report adjusted R^2 in the GOF block?

Report the number of observations in the GOF block?

Report the F-statistic in the GOF block?

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 summary method for the object.

A statistical model object.

Arrange the model terms below each other or beside each other? In a stergm model, the formation and dissolution coefficients can be arranged in two columns of the table.

Report the coefficients for the formation process in a STERGM?

Report the coefficients for the dissolution process in a STERGM?

Report the number of vertices in a STERGM?

Report Akaike's Information Criterion (AIC) in the GOF block?

Report the Bayesian Information Criterion (BIC) in the GOF block?

Report the log likelihood in the GOF block?

Custom parameters, which are handed over to subroutines, in this case to the summary method for the object.

A statistical model object.

Report R^2 in the GOF block?

Report adjusted R^2 in the GOF block?

Report the number of observations in the GOF block?

Report the F-statistic in the GOF block?

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.

A statistical model object.

Report Akaike's Information Criterion (AIC) in the GOF block?

Report the Bayesian Information Criterion (BIC) in the GOF block?

Report the log likelihood in the GOF block?

Report the deviance?

Report the number of observations in the GOF block?

Custom parameters, which are handed over to subroutines, in this case to the summary method for the object.

A statistical model object.

Report Akaike's Information Criterion (AIC) in the GOF block?

Report the Bayesian Information Criterion (BIC) in the GOF block?

Report the log likelihood in the GOF block?

Report the deviance?

Report the number of observations in the GOF block?

Custom parameters, which are handed over to subroutines, in this case to the summary method for the object.

A statistical model object.

Report Akaike's Information Criterion (AIC) in the GOF block?

Report the Bayesian Information Criterion (BIC) in the GOF block?

Report the log likelihood in the GOF block?

Report the deviance?

Report the dispersion parameter?

Report the number of observations in the GOF block?

Custom parameters, which are handed over to subroutines, in this case to the summary method for the object.

A statistical model object.

Report R^2 in the GOF block?

Report adjusted R^2 in the GOF block?

Report the number of observations in the GOF block?

Arrange the model terms below each other or beside each other, in separate columns?

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 summary method for the object.

A statistical model object.

Custom parameters, which are handed over to subroutines. Currently not in use.

A statistical model object.

Report Akaike's Information Criterion (AIC) in the GOF block?

Report the Bayesian Information Criterion (BIC) in the GOF block?

Report the log likelihood in the GOF block?

Report the deviance?

Report the number of observations in the GOF block?

Report the total, right-censored, left-censored, and uncensored number of observations?

Report the Wald statistic?

Custom parameters, which are handed over to subroutines, in this case to the summary method for the object.

A statistical model object.

Report the number of observations in the GOF block?

Report the log likelihood in the GOF block?

Report Akaike's Information Criterion (AIC) in the GOF block?

Report the Bayesian Information Criterion (BIC) in the GOF block?

Custom parameters, which are handed over to subroutines. Currently not in use.

A statistical model object.

Report the log likelihood in the GOF block?

Report the degrees of freedom?

Report the number of observations in the GOF block?

Custom parameters, which are handed over to subroutines. Currently not in use.

A statistical model object.

Report Akaike's Information Criterion (AIC) in the GOF block?

Report the log likelihood in the GOF block?

Report likelihood ratio test?

Report the number of observations in the GOF block?

Report the number of events in the GOF block?

Report the total time at risk (in event-history models)?

Custom parameters, which are handed over to subroutines. Currently not in use.

A statistical model object.

Report RMSEA and other GOF statistics?

Report the number of observations in the GOF block?

Report AIC?

Report BIC?

Custom parameters, which are handed over to subroutines. Currently not in use.

A statistical model object.

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.

Report the count parameters in the coefficients block (before the binary part for the zeros)?

Should the binary part of the model be included in the coefficients block (after the count parameters)?

Report Akaike's Information Criterion (AIC) in the GOF block?

Report the log likelihood in the GOF block?

Report the number of observations in the GOF block?

Custom parameters, which are handed over to subroutines, in this case to the summary method for the object.

A list of statistical models.

Arguments to be passed over to the extract function, such as include.nobs or include.aic. Details are provided in the documentation of the extract function.

A numeric vector of cut-offs, with a maximum of four numbers.

The character to repeat for the first three levels of significance.

The character for the fourth level of significance.

Confidence intervals instead of standard errors?

The null hypothesis value, for example 0 (the normal case) or 1 (e.g., with exponentiated coefficients). A star is added if this value is outside the confidence interval.

The output type of the note. This can be "ascii", "latex", or "html".

A statistical model or a list of statistical models. Lists of models can be specified as l = list(model.1, model.2, ...). Different object types can also be mixed.

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 htmlreg function, an HTML table can be written to a file with the extension .doc and opened with MS Word. The table can then be simply copied into any Word document, retaining the formatting of the table. Note that LibreOffice can import only plain HTML; CSS decorations are not supported; the resulting tables do not retain the full formatting in LibreOffice.

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 single.row = TRUE is activated, however, both coefficient and standard error are placed in a single table cell in the same line.

The significance levels to be used to draw stars. Between 0 and 4 threshold values can be provided as a numeric vector. For example, stars = numeric(0) will not print any stars and will not print any note about significance levels below the table. stars = 0.05 will attach one single star to all coefficients where the p value is below 0.05. stars = c(0.001, 0.01, 0.05, 0.1) will print one, two, or three stars, or a symbol as specified by the symbol argument depending on the p-values.

An optional named list of multi-column headers that are placed above the model names. For example, custom.header = list("abc" = 1:3, "ef" = 4:5) will add the label "abc" to the first three models and "ef" to the fourth and fifth model. The column with coefficient names and any custom columns added by the "custom.columns" argument are not counted towards these positions. If booktabs = TRUE, \cmidrule rules are added below the respective labels; otherwise \cline lines are used.

A character vector of labels for the models. By default, the models are named "Model 1", "Model 2", etc. Specifying model.names = c("My name 1", "My name 2") etc. overrides the default behavior.

By default, texreg uses the coefficient names which are stored in the models. The custom.coef.names argument can be used to replace them by other character strings in the order of appearance. For example, if a table shows a total of three different coefficients (including the intercept), the argument custom.coef.names = c("Intercept", "variable 1", "variable 2") will replace their names in this order.

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 NA value, the original name of the coefficient is kept. For example, custom.coef.names = c(NA, "age", NA) will only replace the second coefficient name and leave the first and third name as they are in the original model.

See also custom.coef.map for an easier and more comprehensive way to rename, omit, and reorder coefficients.

The custom.coef.map argument can be used to select, omit, rename, and reorder coefficients.

Users must supply a named list of this form: list("x" = "First variable", "y" = NA, "z" = "Third variable"). With that particular example of custom.coef.map,

1. coefficients will be presented in order: "x", "y", "z".

2. variable "x" will appear as "First variable", variable "y" will appear as "y", and variable "z" will appear as "Third variable".

3. all variables not named "x", "y", or "z" will be omitted from the table.

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.coef.names argument, but for the GOF values. NA values can be included where the original GOF name should be kept.

A named list of vectors for new lines at the beginning of the GOF block of the table. For example, list("Random effects" = c("YES", "YES", "NO"), Observations = c(25, 25, 26)) would insert two new rows into the table, at the beginning of the GOF block (i.e., after the coefficients). The rows can contain integer, numeric, or character objects. Note that this argument is processed after the custom.gof.names argument (meaning custom.gof.names should not include any of the new GOF rows) and before the reorder.gof argument (meaning that the new GOF order specified there should contain values for the new custom GOF rows). Arguments for custom columns are not affected because they only insert columns into the coefficient block.

With this argument, a replacement text for the significance note below the table can be provided. If an empty character object is provided (custom.note = ""), the note will be omitted completely. If some character string is provided (e.g., custom.note = "My note"), the significance legend is replaced by My note. The original significance legend can be included by inserting the %stars wildcard. For example, a custom note can be added right after the significance legend by providing custom.note = "%stars. My note.".

If the threeparttable argument is used, any note should be preceded by "\\item", for example "\\item %stars. \\item Second note. \\item Third note.", and it is possible to create line breaks in the formatted table by including "\\\\" and line breaks in the LaTeX code by including "\n", for example "\n\\item %stars.\\\\\n\\item Second line.\n".

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 digits argument in the round function of the base package.

Most journals require leading zeros of coefficients and standard errors (for example, 0.35). This is also the default texreg behavior. Some journals, however, require omission of leading zeros (for example, .35). This can be achieved by setting leading.zero = FALSE.

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 star.symbol = "*". Note that some other modifications are recommended for usage with knitr in combination with Markdown or HTML (see the inline.css, doctype, html.tag, head.tag, and body.tag arguments in the htmlreg function).

If four threshold values are handed over to the stars argument, p-values smaller than the largest threshold value but larger than the second-largest threshold value are denoted by this symbol. The default symbol is "\\cdot" for the LaTeX dot, "·" for the HTML dot, or simply "." for the ASCII dot. If the texreg function is used, any other mathematical LaTeX symbol or plain text symbol can be used, for example symbol = "\\circ" for a small circle (note that backslashes must be escaped). If the htmlreg function is used, any other HTML character or symbol can be used. For the screenreg function, only plain text characters can be used.

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.coef = list(c(0.1, 0.2, 0.3), c(0.05, 0.06, 0.07)). If there is only one model, custom values can be provided as a plain vector (not embedded in a list). For example: override.coef = c(0.05, 0.06, 0.07).

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.se = list(c(0.1, 0.2, 0.3), c(0.05, 0.06, 0.07)). If there is only one model, custom values can be provided as a plain vector (not embedded in a list).For example: override.se = c(0.05, 0.06, 0.07). Overriding standard errors can be useful for the implementation of robust SEs, for example.

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.pvalues = list(c(0.1, 0.2, 0.3), c(0.05, 0.06, 0.07)). If there is only one model, custom values can be provided as a plain vector (not embedded in a list). For example: override.pvalues = c(0.05, 0.06, 0.07). Overriding p-values can be useful for the implementation of robust SEs and p-values, for example.

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 argument, the standard errors and p-values as well as the ci.force argument are ignored.

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.ci.low argument, the standard errors and p values as well as the ci.force argument are ignored.

A character string which is used as a regular expression to remove coefficient rows from the table. For example, omit.coef = "group" deletes all coefficient rows from the table where the name of the coefficient contains the character sequence "group". More complex regular expressions can be used to filter out several kinds of model terms, for example omit.coef = "(thresh)|(ranef)" to remove all model terms matching either "thresh" or "ranef". The omit.coef argument is processed after the custom.coef.names argument, so the regular expression should refer to the custom coefficient names. To omit GOF entries instead of coefficient entries, use the custom arguments of the extract functions instead (see the help entry of the extract function.

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.coef = c(3, 2, 1) will put the third coefficient in the first row and the first coefficient in the third row. Reordering can be sensible because interaction effects are often added to the end of the model output although they were specified earlier in the model formula. Note: Reordering takes place after processing custom coefficient names and after omitting coefficients, so the custom.coef.names and omit.coef arguments should follow the original order.

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, reorder.gof = c(3, 2, 1) will exchange the first and the third row. Note: Reordering takes place after processing custom GOF names and after adding new custom GOF rows, so the custom.gof.names and custom.gof.rows arguments should follow the original order, and the reorder.gof argument should contain values for any rows that are added through the custom.gof.rows argument.

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 argument accepts either a logical value indicating whether all models or none of the models should be forced to report confidence intervals (ci.force = TRUE for all and ci.force = FALSE for none) or a vector of logical values indicating for each model separately whether the model should be forced to report confidence intervals (e.g., ci.force = c(FALSE, TRUE, FALSE)). Confidence intervals are computed using the standard normal distribution (z-values based on the qnorm function). The t-distribution is currently not supported because this would require each extract method to have an additional argument for the degrees of freedom.

If the ci.force argument is used to convert standard errors to confidence intervals, what confidence level should be used? By default, 0.95 is used (i.e., an alpha value of 0.05).

If confidence intervals are reported, the ci.test argument specifies the reference value to establish whether a coefficient/CI is significant. The default value ci.test = 0, for example, will attach a significance star to coefficients if the confidence interval does not contain 0. A value of ci.test = 1 could be useful if coefficients are provided on the odds-ratio scale, for example. If no star should be printed at all, ci.test = NA can be used. It is possible to provide a single value for all models or a vector with a separate value for each model. The ci.test argument works both for models with native support for confidence intervals and in cases where the ci.force argument is used.

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: groups = list("first group" = 1:4, "second group" = 7:8).

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.columns = list(type = c("a", "b", "c"), 1:3) will add two columns; the first one is labeled while the second one is not. Note that the numeric elements of the second column will be converted to character objects in this example. The consequence is that decimal alignment with the dcolumn package is switched off in these columns. Note that this argument is processed after any arguments that affect the number of rows.

An optional integer vector of positions for the columns given in the custom.columns argument. For example, if there are three custom columns, custom.col.pos = c(1, 3, 3) will insert the first custom column before the first column of the original table and the remaining two custom columns after the second column of the original table. By default, all custom columns are placed after the first column, which usually contains the coefficient names.

The p-value threshold below which the coefficient shall be formatted in a bold font. For example, bold = 0.05 will cause all coefficients that are significant at the 95% level to be formatted in bold. Note that this is not compatible with the dcolumn or siunitx arguments in the texreg function. If both bold and dcolumn or siunitx are TRUE, dcolumn and siunitx are switched off, and a warning message appears. Note also that it is advisable to use stars = FALSE together with the bold argument because having both bolded coefficients and significance stars usually does not make any sense.

Should the table be horizontally aligned at the center of the page?

Set the caption of the table.

Should the caption of the table be placed above the table? By default, it is placed below the table.

Should the CSS stylesheets be embedded directly in the code of the table (inline.css = TRUE), or should the CSS stylesheets be enclosed in the <head> tag, that is, separated from the table code (inline.css = FALSE)? Having inline CSS code makes the code of the table more complex, but sometimes it may be helpful when only the table shall be printed, without the head of the HTML file (for example when the table is embedded in a knitr report). As a rule of thumb: use inline CSS if the table is not saved to a file.

Should the first line of the HTML code contain the DOCTYPE definition? If TRUE, the HTML 4 TRANSITIONAL version is used. If FALSE, no DOCTYPE will be included. Omitting the DOCTYPE can be helpful when the knitr package is used to generate HTML code because knitr requires only the plain table, not the whole HTML document including the document type declaration. Including the DOCTYPE can be helpful when the code is saved to a file, for example as an MS Word document.

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.

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.

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.

Characters used for indentation of the HTML code. By default, indentation = "" uses no indentation. Any number of spaces or characters can be used instead. For example, indentation = " " uses two spaces of (additional) indentation for each subelement.

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 table.margin = 0.

The space on the left and right of each table cell in pixels.

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., "black").

The line width at the top and bottom of the table in pixels. Can be outer.rules = 0 to omit outer lines.

The horizontal line width before and after the coefficient block of the table in pixels. Can be outer.rules = 0 to omit inner lines.

Custom options to be passed on to the extract function. For example, most extract methods provide custom options for the inclusion or exclusion of specific goodness-of-fit statistics. See the help entries of extract for more information.

A statistical model or a list of statistical models. Lists of models can be specified as l = list(model.1, model.2, ...). Different object types can also be mixed.

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 single.row = TRUE is activated, however, both coefficient and standard error are placed in a single table cell in the same line.

The significance levels to be used to draw stars. Between 0 and 4 threshold values can be provided as a numeric vector. For example, stars = numeric(0) will not print any stars and will not print any note about significance levels below the table. stars = 0.05 will attach one single star to all coefficients where the p value is below 0.05. stars = c(0.001, 0.01, 0.05, 0.1) will print one, two, or three stars, or a symbol as specified by the symbol argument depending on the p-values.

A character vector of labels for the models. By default, the models are named "Model 1", "Model 2", etc. Specifying model.names = c("My name 1", "My name 2") etc. overrides the default behavior.

By default, texreg uses the coefficient names which are stored in the models. The custom.coef.names argument can be used to replace them by other character strings in the order of appearance. For example, if a table shows a total of three different coefficients (including the intercept), the argument custom.coef.names = c("Intercept", "variable 1", "variable 2") will replace their names in this order.

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 NA value, the original name of the coefficient is kept. For example, custom.coef.names = c(NA, "age", NA) will only replace the second coefficient name and leave the first and third name as they are in the original model.

See also custom.coef.map for an easier and more comprehensive way to rename, omit, and reorder coefficients.

The custom.coef.map argument can be used to select, omit, rename, and reorder coefficients.

Users must supply a named list of this form: list("x" = "First variable", "y" = NA, "z" = "Third variable"). With that particular example of custom.coef.map,

1. coefficients will be presented in order: "x", "y", "z".

2. variable "x" will appear as "First variable", variable "y" will appear as "y", and variable "z" will appear as "Third variable".

3. all variables not named "x", "y", or "z" will be omitted from the table.

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.coef.names argument, but for the GOF values. NA values can be included where the original GOF name should be kept.

A named list of vectors for new lines at the beginning of the GOF block of the table. For example, list("Random effects" = c("YES", "YES", "NO"), Observations = c(25, 25, 26)) would insert two new rows into the table, at the beginning of the GOF block (i.e., after the coefficients). The rows can contain integer, numeric, or character objects. Note that this argument is processed after the custom.gof.names argument (meaning custom.gof.names should not include any of the new GOF rows) and before the reorder.gof argument (meaning that the new GOF order specified there should contain values for the new custom GOF rows). Arguments for custom columns are not affected because they only insert columns into the coefficient block.

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 digits argument in the round function of the base package.

Most journals require leading zeros of coefficients and standard errors (for example, 0.35). This is also the default texreg behavior. Some journals, however, require omission of leading zeros (for example, .35). This can be achieved by setting leading.zero = FALSE.

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 star.symbol = "*". Note that some other modifications are recommended for usage with knitr in combination with Markdown or HTML (see the inline.css, doctype, html.tag, head.tag, and body.tag arguments in the htmlreg function).

If four threshold values are handed over to the stars argument, p-values smaller than the largest threshold value but larger than the second-largest threshold value are denoted by this symbol. The default symbol is "\\cdot" for the LaTeX dot, "·" for the HTML dot, or simply "." for the ASCII dot. If the texreg function is used, any other mathematical LaTeX symbol or plain text symbol can be used, for example symbol = "\\circ" for a small circle (note that backslashes must be escaped). If the htmlreg function is used, any other HTML character or symbol can be used. For the screenreg function, only plain text characters can be used.

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.coef = list(c(0.1, 0.2, 0.3), c(0.05, 0.06, 0.07)). If there is only one model, custom values can be provided as a plain vector (not embedded in a list). For example: override.coef = c(0.05, 0.06, 0.07).

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.se = list(c(0.1, 0.2, 0.3), c(0.05, 0.06, 0.07)). If there is only one model, custom values can be provided as a plain vector (not embedded in a list).For example: override.se = c(0.05, 0.06, 0.07). Overriding standard errors can be useful for the implementation of robust SEs, for example.

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.pvalues = list(c(0.1, 0.2, 0.3), c(0.05, 0.06, 0.07)). If there is only one model, custom values can be provided as a plain vector (not embedded in a list). For example: override.pvalues = c(0.05, 0.06, 0.07). Overriding p-values can be useful for the implementation of robust SEs and p-values, for example.

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 argument, the standard errors and p-values as well as the ci.force argument are ignored.

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.ci.low argument, the standard errors and p values as well as the ci.force argument are ignored.

A character string which is used as a regular expression to remove coefficient rows from the table. For example, omit.coef = "group" deletes all coefficient rows from the table where the name of the coefficient contains the character sequence "group". More complex regular expressions can be used to filter out several kinds of model terms, for example omit.coef = "(thresh)|(ranef)" to remove all model terms matching either "thresh" or "ranef". The omit.coef argument is processed after the custom.coef.names argument, so the regular expression should refer to the custom coefficient names. To omit GOF entries instead of coefficient entries, use the custom arguments of the extract functions instead (see the help entry of the extract function.

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.coef = c(3, 2, 1) will put the third coefficient in the first row and the first coefficient in the third row. Reordering can be sensible because interaction effects are often added to the end of the model output although they were specified earlier in the model formula. Note: Reordering takes place after processing custom coefficient names and after omitting coefficients, so the custom.coef.names and omit.coef arguments should follow the original order.

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, reorder.gof = c(3, 2, 1) will exchange the first and the third row. Note: Reordering takes place after processing custom GOF names and after adding new custom GOF rows, so the custom.gof.names and custom.gof.rows arguments should follow the original order, and the reorder.gof argument should contain values for any rows that are added through the custom.gof.rows argument.

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 argument accepts either a logical value indicating whether all models or none of the models should be forced to report confidence intervals (ci.force = TRUE for all and ci.force = FALSE for none) or a vector of logical values indicating for each model separately whether the model should be forced to report confidence intervals (e.g., ci.force = c(FALSE, TRUE, FALSE)). Confidence intervals are computed using the standard normal distribution (z-values based on the qnorm function). The t-distribution is currently not supported because this would require each extract method to have an additional argument for the degrees of freedom.

If the ci.force argument is used to convert standard errors to confidence intervals, what confidence level should be used? By default, 0.95 is used (i.e., an alpha value of 0.05).

If confidence intervals are reported, the ci.test argument specifies the reference value to establish whether a coefficient/CI is significant. The default value ci.test = 0, for example, will attach a significance star to coefficients if the confidence interval does not contain 0. A value of ci.test = 1 could be useful if coefficients are provided on the odds-ratio scale, for example. If no star should be printed at all, ci.test = NA can be used. It is possible to provide a single value for all models or a vector with a separate value for each model. The ci.test argument works both for models with native support for confidence intervals and in cases where the ci.force argument is used.

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: groups = list("first group" = 1:4, "second group" = 7:8).

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.columns = list(type = c("a", "b", "c"), 1:3) will add two columns; the first one is labeled while the second one is not. Note that the numeric elements of the second column will be converted to character objects in this example. The consequence is that decimal alignment with the dcolumn package is switched off in these columns. Note that this argument is processed after any arguments that affect the number of rows.

An optional integer vector of positions for the columns given in the custom.columns argument. For example, if there are three custom columns, custom.col.pos = c(1, 3, 3) will insert the first custom column before the first column of the original table and the remaining two custom columns after the second column of the original table. By default, all custom columns are placed after the first column, which usually contains the coefficient names.

Custom options to be passed on to the extract function. For example, most extract methods provide custom options for the inclusion or exclusion of specific goodness-of-fit statistics. See the help entries of extract for more information.

Arguments to be handed over to the texreg, htmlreg, screenreg, or matrixreg function. See the respective help page for details.

A statistical model or a list of statistical models. Lists of models can be specified as l = list(model.1, model.2, ...). Different object types can also be mixed.

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 single.row = TRUE is activated, however, both coefficient and standard error are placed in a single table cell in the same line.

The significance levels to be used to draw stars. Between 0 and 4 threshold values can be provided as a numeric vector. For example, stars = numeric(0) will not print any stars and will not print any note about significance levels below the table. stars = 0.05 will attach one single star to all coefficients where the p value is below 0.05. stars = c(0.001, 0.01, 0.05, 0.1) will print one, two, or three stars, or a symbol as specified by the symbol argument depending on the p-values.

A character vector of labels for the models. By default, the models are named "Model 1", "Model 2", etc. Specifying model.names = c("My name 1", "My name 2") etc. overrides the default behavior.

By default, texreg uses the coefficient names which are stored in the models. The custom.coef.names argument can be used to replace them by other character strings in the order of appearance. For example, if a table shows a total of three different coefficients (including the intercept), the argument custom.coef.names = c("Intercept", "variable 1", "variable 2") will replace their names in this order.

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 NA value, the original name of the coefficient is kept. For example, custom.coef.names = c(NA, "age", NA) will only replace the second coefficient name and leave the first and third name as they are in the original model.

See also custom.coef.map for an easier and more comprehensive way to rename, omit, and reorder coefficients.

The custom.coef.map argument can be used to select, omit, rename, and reorder coefficients.

Users must supply a named list of this form: list("x" = "First variable", "y" = NA, "z" = "Third variable"). With that particular example of custom.coef.map,

1. coefficients will be presented in order: "x", "y", "z".

2. variable "x" will appear as "First variable", variable "y" will appear as "y", and variable "z" will appear as "Third variable".

3. all variables not named "x", "y", or "z" will be omitted from the table.

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.coef.names argument, but for the GOF values. NA values can be included where the original GOF name should be kept.