Package index • pbkrtest

Model comparison ~
`KRmodcomp()`	F-test and degrees of freedom based on Kenward-Roger approximation
`PBrefdist()`	Calculate reference distribution using parametric bootstrap
`PBFmodcomp()` `PBmodcomp()` `seqPBmodcomp()`	Model comparison using parametric bootstrap methods.
`SATmodcomp()`	F-test and degrees of freedom based on Satterthwaite approximation
`X2modcomp()`	Chisq test
Data sets ~
`beets`	Sugar beets data
`budworm`	Budworm data
Others These are functions not mentioned above.
`anovax()` `print(<anovax>)`	anova like function
`anovax_list()`	Various different tests for model comparison
`comodex()`	Model comparison
`compare_column_space()`	Compare column spaces
`get_Lb_ddf()` `get_ddf_Lb()` `Lb_ddf()` `ddf_Lb()`	Adjusted denominator degrees of freedom for linear estimate for linear mixed model.
`get_vary()`	Get variance covariance matrix for lmerMod and gls
`gls_cov_matrix()`	Returns covariance matrix for gls model
`gls_varcorr()`	Variance and correlation parameters from gls object
`internal-pbkrtest`	pbkrtest internal
`internal` `print.PBmodcomp` `print.summary_PBmodcomp` `summary.PBmodcomp` `plot.PBmodcomp` `summary.KRmodcomp` `print.KRmodcomp` `KRmodcomp_init` `KRmodcomp_init.lmerMod` `KRmodcomp_init.mer` `as.data.frame.XXmodcomp` `tidy`	Internal functions for the pbkrtest package
`vcovAdj()`	Adjusted covariance matrix for linear mixed models according to Kenward and Roger
`model2restriction_matrix()` `restriction_matrix2model()` `make_model_matrix()` `make_restriction_matrix()`	Conversion between a model object and a restriction matrix
`refit(<glm>)`	Refit linear model / generalized linear model to new response
`refit_gls()`	Refit a gls object to new response variable
`simulate(<gls>)`	Simulate data for 'gls' object
Complete reference
`anovax()` `print(<anovax>)`	anova like function
`anovax_list()`	Various different tests for model comparison
`comodex()`	Model comparison
`compare_column_space()`	Compare column spaces
`beets`	Sugar beets data
`budworm`	Budworm data
`get_Lb_ddf()` `get_ddf_Lb()` `Lb_ddf()` `ddf_Lb()`	Adjusted denominator degrees of freedom for linear estimate for linear mixed model.
`get_vary()`	Get variance covariance matrix for lmerMod and gls
`gls_cov_matrix()`	Returns covariance matrix for gls model
`gls_varcorr()`	Variance and correlation parameters from gls object
`internal-pbkrtest`	pbkrtest internal
`internal` `print.PBmodcomp` `print.summary_PBmodcomp` `summary.PBmodcomp` `plot.PBmodcomp` `summary.KRmodcomp` `print.KRmodcomp` `KRmodcomp_init` `KRmodcomp_init.lmerMod` `KRmodcomp_init.mer` `as.data.frame.XXmodcomp` `tidy`	Internal functions for the pbkrtest package
`vcovAdj()`	Adjusted covariance matrix for linear mixed models according to Kenward and Roger
`KRmodcomp()`	F-test and degrees of freedom based on Kenward-Roger approximation
`model2restriction_matrix()` `restriction_matrix2model()` `make_model_matrix()` `make_restriction_matrix()`	Conversion between a model object and a restriction matrix
`PBrefdist()`	Calculate reference distribution using parametric bootstrap
`PBFmodcomp()` `PBmodcomp()` `seqPBmodcomp()`	Model comparison using parametric bootstrap methods.
`refit(<glm>)`	Refit linear model / generalized linear model to new response
`refit_gls()`	Refit a gls object to new response variable
`SATmodcomp()`	F-test and degrees of freedom based on Satterthwaite approximation
`simulate(<gls>)`	Simulate data for 'gls' object
`X2modcomp()`	Chisq test

Reference

Model comparison

Data sets

Others

Complete reference