This document provides an introduction to mixed models. It uses lme4 as the primary tool, but demonstrates others. Topics include random intercept and slope models, discussion of crossed vs. nested random effects, some common extensions (e.g. generalized linear mixed models), Bayesian tools, and other models that deal with dependency in the data.
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Covers the basics of mixed models, mostly using @lme4
m-clark/mixed-models-with-R
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