WeMix v2.2.1


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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.

Functions in WeMix

Name Description
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.
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Last month downloads


Date 2019-03-14
LinkingTo Rcpp, RcppArmadillo
License GPL-2
VignetteBuilder knitr
LazyData true
ByteCompile true
Note This publication was prepared for NCES under Contract No. ED-IES-12-D-0002 with American Institutes for Research. Mention of trade names, commercial products, or organizations does not imply endorsement by the U.S. government.
RoxygenNote 6.1.1
Encoding UTF-8
NeedsCompilation yes
Packaged 2019-03-14 14:57:20 UTC; ckelley
Repository CRAN
Date/Publication 2019-03-14 21:44:19 UTC

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