Package: mlmtools 1.1.0

mlmtools: Multi-Level Model Assessment Kit

Multilevel models (mixed effects models) are the statistical tool of choice for analyzing multilevel data (Searle et al, 2009). These models account for the correlated nature of observations within higher level units by adding group-level error terms that augment the singular residual error of a standard OLS regression. Multilevel and mixed effects models often require specialized data pre-processing and further post-estimation derivations and graphics to gain insight into model results. The package presented here, 'mlmtools', is a suite of pre- and post-estimation tools for multilevel models in 'R'. Package implements post-estimation tools designed to work with models estimated using 'lme4''s (Bates et al., 2014) lmer() function, which fits linear mixed effects regression models. Searle, S. R., Casella, G., & McCulloch, C. E. (2009, ISBN:978-0470009598). Bates, D., Mächler, M., Bolker, B., & Walker, S. (2014) <doi:10.18637/jss.v067.i01>.

Authors:Laura Jamison [aut, cre], Jessica Mazen [aut], Erik Ruzek [aut], Gus Sjobeck [ctb]

mlmtools_1.1.0.tar.gz
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mlmtools.pdf |mlmtools.html
mlmtools/json (API)

# Install 'mlmtools' in R:
install.packages('mlmtools', repos = c('https://lkjamison.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/lkjamison/mlmtools/issues

On CRAN:

3.40 score 1 stars 5 scripts 151 downloads 10 exports 34 dependencies

Last updated 2 years agofrom:a6bb2233c3. Checks:OK: 6 ERROR: 1. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 14 2024
R-4.5-winOKOct 14 2024
R-4.5-linuxERROROct 14 2024
R-4.4-winOKOct 14 2024
R-4.4-macOKOct 14 2024
R-4.3-winOKOct 14 2024
R-4.3-macOKOct 14 2024

Exports:betweenPlotcaterpillarPlotcenterICCmlevelComparelevelComparePlotmlm_assumptionsrsqmlmvarComparewithinPlot

Dependencies:bootclicolorspacefansifarverggplot2gluegtableisobandlabelinglatticelifecyclelme4magrittrMASSMatrixmgcvminqamunsellnlmenloptrpillarpkgconfigR6RColorBrewerRcppRcppEigenrlangscalestibbleutf8vctrsviridisLitewithr