Weighted Mixed-Effects Models, using Multilevel Pseudo Maximum Likelihood Estimation

Run mixed-effects models that include weights at every level. The WeMix package fits a Weighted Mixed model, also known as a multilevel, mixed, or hierarchical linear model (HLM). The weights could be inverse selection probabilities, such as those developed for an education survey where schools are sampled probabilistically, and then students inside of those schools are sampled probabilistically. Although mixed-effects models are already available in R, WeMix is unique in implementing methods for mixed models using weights at multiple levels. The model is fit using adaptive quadrature.


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install.packages("WeMix")

2.2.1 by Claire Kelley, 5 days ago


Browse source code at https://github.com/cran/WeMix


Authors: Paul Bailey , Claire Kelley , Trang Nguyen , Huade Huo.


Documentation:   PDF Manual  


GPL-2 license


Imports numDeriv, statmod, Rmpfr, NPflow, Rcpp

Depends on lme4

Suggests testthat, knitr, rmarkdown, EdSurvey

Linking to Rcpp, RcppArmadillo


Imported by EdSurvey.


See at CRAN