R: Diagnostic tools for hierarchical (multilevel) linear models
HLMdiag
R Documentation
Diagnostic tools for hierarchical (multilevel) linear models
Description
HLMdiag provides a suite of diagnostic tools for hierarchical
(multilevel) linear models fit using lmer or
lme. These tools are grouped below by purpose.
See the help documentation for additional information
about each function.
Details
Residual analysis
HLMdiag's HLMresid function provides a convenient
wrapper to obtain residuals at each level of a hierarchical
linear model. In addition to being a wrapper function for functions
implemented in the lme4 package, HLMresid provides access
to the marginal and least squares residuals (through LSresids)
that were not previously implemented.
Influence analysis
Influence on fitted values
HLMdiag provides leverage that calculates the influence
that observations/groups have on the fitted values (leverage).
For mixed/hierarchical models leverage can be decomposed into two parts: the
fixed part and the random part. We refer the user to the references
cited in the help documentation for additional explanation.
Influence on fixed effects estimates
HLMdiag provides cooks.distance and mdffits
to assess the influence of subsets of observations on the fixed effects.
Influence on precision of fixed effects
HLMdiag provides covratio and covtrace
to assess the influence of subsets of observations on the precision of
the fixed effects.
Influence on variance components
HLMdiag's rvc calculates the relative variance change to
assess the influence of subsets of observations on the variance
components.
Graphics
HLMdiag also strives to make graphical assessment easier in the
ggplot2 framework by providing dotplots for influence diagnostics
(dotplot_diag), grouped Q-Q plots (group_qqnorm),
and Q-Q plots that combine the functionality of qqnorm and
qqline (ggplot_qqnorm).