Over the last twenty years there have been numerous developments in diagnostic pro- cedures for hierarchical linear models; however, these procedures are not widely imple- mented in statistical software packages, and those packages that do contain a complete framework for model assessment are not open source. The lack of availability of diagnostic procedures for hierarchical linear models has limited their adoption in statistical practice. The R package HLMdiag provides diagnostic tools targeting all aspects and levels of continuous response hierarchical linear models with strictly nested dependence structures fit using the lmer() function in the lme4 package. In this paper we discuss the tools implemented in HLMdiag for both residual and influence analysis.
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