In the social sciences the prevalence of clustered, correlated, and/or repeatedly measured
data is very common. Modeling such data have classically involved the use of techniques
such as the repeated measured analysis of variance (ANOVA) with correction factors
applied to account for violations of model assumptions. More recently multi-level or
hierarchical linear models have been brought to bear on modeling these kind of data given
their flexibility. One of the most popular packages used for this purpose is the powerful lme4 …