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, the Bayesian Information Criterion, the explained deviance, or the F-test of the change in R².

Version: 2.11
Depends: R (≥ 3.2)
Imports: graphics, lme4, methods, mgcv, nlme, stats, utils
Suggests: GLMMadaptive, MASS, gamm4, glmertree, glmmTMB, knitr, lmerTest, nnet, ordinal, parallel, partykit, pbkrtest, rmarkdown, testthat
Published: 2023-10-25
Author: Cesko C. Voeten ORCID iD [aut, cre]
Maintainer: Cesko C. Voeten <cvoeten at gmail.com>
BugReports: https://gitlab.com/cvoeten/buildmer/-/issues
License: FreeBSD
NeedsCompilation: no
Materials: ChangeLog
In views: MixedModels
CRAN checks: buildmer results

Documentation:

Reference manual: buildmer.pdf
Vignettes: Using 'buildmer' to automatically find & compare maximal (mixed) models

Downloads:

Package source: buildmer_2.11.tar.gz
Windows binaries: r-devel: buildmer_2.11.zip, r-release: buildmer_2.11.zip, r-oldrel: buildmer_2.11.zip
macOS binaries: r-release (arm64): buildmer_2.11.tgz, r-oldrel (arm64): buildmer_2.11.tgz, r-release (x86_64): buildmer_2.11.tgz
Old sources: buildmer archive

Reverse dependencies:

Reverse suggests: permutes

Linking:

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