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mlmtools  

Multi-Level Model Assessment Kit
View on CRAN: Click here


Download and install mlmtools package within the R console
Install from CRAN:
install.packages("mlmtools")

Install from Github:
library("remotes")
install_github("cran/mlmtools")

Install by package version:
library("remotes")
install_version("mlmtools", "1.0.2")



Attach the package and use:
library("mlmtools")
Maintained by
Laura Jamison
[Scholar Profile | Author Map]
First Published: 2022-09-30
Latest Update: 2022-10-26
Description:
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., M
How to cite:
Laura Jamison (2022). mlmtools: Multi-Level Model Assessment Kit. R package version 1.0.2, https://cran.r-project.org/web/packages/mlmtools. Accessed 30 Apr. 2025.
Previous versions and publish date:
1.0.1 (2022-09-30 09:30)
Other packages that cited mlmtools R package
View mlmtools citation profile
Other R packages that mlmtools depends, imports, suggests or enhances
Complete documentation for mlmtools
Functions, R codes and Examples using the mlmtools R package
Some associated functions: ICCm . betweenPlot . caterpillarPlot . center . instruction . mlm_assumptions . prints . reporting . rsqmlm . varCompare . withinPlot . 
Some associated R codes: ICCm.R . betweenPlot.R . caterpillarPlot.R . center.R . globals.R . instruction.R . mlm_assumptions.R . prints.R . reporting.R . rsqmlm.R . varCompare.R . withinPlot.R .  Full mlmtools package functions and examples
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