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MLMES  

Model-Based Effect Sizes for Multilevel Models
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("MLMES", "0.1.2")



Attach the package and use:
library("MLMES")
Maintained by
Yijun Cheng
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-08-20
Latest Update: 2026-08-20
Description:
Computes model-based effect sizes for fixed-effect coefficients in multilevel (hierarchical) models. The coefficient effect sizes are standardized mean differences from zero (d) and unique variance-explained measures (squared semi-partial correlations, sr2). The package also reports variance components and level-specific and total R-squared values. It supports 2-level and 3-level linear and binary logistic models fitted with 'lme4' (Bates et al., 2015) <doi:10.18637/jss.v067.i01>, and 2-level Gaussian and Bernoulli models fitted with 'brms' (Bürkner, 2017) <doi:10.18637/jss.v080.i01>. Sanders, Konold, and Cheng (in press), "Model-based effect sizes for multilevel linear regression coefficients," Methodology: European Journal of Research Methods for the Behavioral and Social Sciences, describe the 2-level linear-model methods.
How to cite:
Yijun Cheng (2026). MLMES: Model-Based Effect Sizes for Multilevel Models. R package version 0.1.2, https://cran.r-project.org/web/packages/MLMES. Accessed 03 Oct. 2026.
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Complete documentation for MLMES
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Full MLMES package functions and examples
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