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WeMix (version 2.2.1)

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

Description

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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Version

Install

install.packages('WeMix')

Monthly Downloads

613

Version

2.2.1

License

GPL-2

Maintainer

Claire Kelley

Last Published

March 14th, 2019

Functions in WeMix (2.2.1)

calc_lin_lnl_quad_fast

This function calcuates the liklihood of the model using integration by adaptive quadrature
mix

Survey Weighted Mixed-Effects Models
WeMix-package

WeMix: Package to Estimate Weighted Mixed-Effects Models.