robustlmm: Robust Linear Mixed Effects Models

Implements the Robust Scoring Equations estimator to fit linear mixed effects models robustly. Robustness is achieved by modification of the scoring equations combined with the Design Adaptive Scale approach.

Version: 3.1-2
Depends: lme4 (≥ 1.1-9), Matrix (≥ 1.0-13), R (≥ 3.5.0)
Imports: lattice, nlme, methods, robustbase (≥ 0.93), xtable, Rcpp (≥ 0.12.2), fastGHQuad, parallel, rlang, utils
LinkingTo: Rcpp, robustbase, Matrix
Suggests: ggplot2, reshape2, microbenchmark, emmeans (≥ 1.4), estimability, lqmm, rlme, MASS, lemon, RColorBrewer, skewt, fs, dplyr, ggh4x, testthat
Published: 2022-12-08
Author: Manuel Koller
Maintainer: Manuel Koller <kollerma at proton.me>
License: GPL-2
URL: https://github.com/kollerma/robustlmm
NeedsCompilation: yes
SystemRequirements: C++11
Citation: robustlmm citation info
Materials: README
In views: MixedModels, Robust
CRAN checks: robustlmm results

Documentation:

Reference manual: robustlmm.pdf
Vignettes: robustlmm: An R Package for Robust Estimation of Linear Mixed-Effects Models
Replication Code For Simulation Studies

Downloads:

Package source: robustlmm_3.1-2.tar.gz
Windows binaries: r-devel: robustlmm_3.1-1.zip, r-release: robustlmm_3.1-1.zip, r-oldrel: robustlmm_3.1-1.zip
macOS binaries: r-release (arm64): robustlmm_3.1-1.tgz, r-oldrel (arm64): robustlmm_3.1-1.tgz, r-release (x86_64): robustlmm_3.1-1.tgz, r-oldrel (x86_64): robustlmm_3.1-1.tgz
Old sources: robustlmm archive

Reverse dependencies:

Reverse suggests: effects, insight, marginaleffects

Linking:

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