Linear Mixed Effects Modeling in R
Mixed-effect models, multilevel models, hierarchical linear models – all refer to a class of statistical models used to analyze correlated data. Such data include repeated measurements, longitudinal measurements and clustered observations. In this workshop we introduce the basics of mixed-effect modeling with an emphasis on implementation and interpretation. Examples will be given in R using the lme4 package. Previous experience with R and linear regression will be helpful but not required.
Instructor: Clay Ford
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