buildmer: Stepwise Elimination and Term Reordering for Mixed-Effects Regression

Finds the largest possible regression model that will still converge for various types of regression analyses (including mixed models and generalized additive models) and then optionally performs stepwise elimination similar to the forward and backward effect selection methods in SAS, based on the change in log-likelihood or its significance, Akaike's Information Criterion, or the Bayesian Information Criterion.

Version: 1.2.1
Depends: R (≥ 3.2)
Imports: methods, mgcv, lme4, plyr, stats, utils
Suggests: JuliaCall, MASS, gamm4, glmertree, glmmTMB, knitr, lmerTest, nlme, nnet, parallel, pbkrtest, rmarkdown
Published: 2019-09-03
Author: Cesko C. Voeten [aut, cre]
Maintainer: Cesko C. Voeten <cvoeten at gmail.com>
BugReports: https://github.com/cvoeten/buildmer/issues
License: FreeBSD
NeedsCompilation: no
Materials: ChangeLog
CRAN checks: buildmer results

Downloads:

Reference manual: buildmer.pdf
Vignettes: Using ‘buildmer’ to automatically find & compare maximal (mixed) models
Package source: buildmer_1.2.1.tar.gz
Windows binaries: r-devel: buildmer_1.2.1.zip, r-release: buildmer_1.2.1.zip, r-oldrel: buildmer_1.2.1.zip
OS X binaries: r-release: buildmer_1.2.1.tgz, r-oldrel: buildmer_1.2.1.tgz
Old sources: buildmer archive

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