compare_eb_ls
(Package: HLMdiag) :
Visually comparing shrinkage and LS estimates
This function creates a plot (using qplot()) where the shrinkage estimate appears on the horizontal axis and the LS estimate appears on the vertical axis.
These functions calculate measures of the change in the fixed effects estimates based on the deletetion of an observation, or group of observations, for a hierarchical linear model fit using lmer.
This is a function that can be used to create (modified) dotplots for the diagnostic measures. The plot allows the user to understand the distribution of the diagnostic measure and visually identify unusual cases.
This function calculates reduced dimensional rotated random effects. The rotation reduces the influence of the residuals from other levels of the model so that distributional assessment of the resulting random effects is possible.
HLMresid is a function that extracts residuals from a hierarchical linear model fit using lmer. That is, it is a unified framework that extracts/calculates residuals from mer or lmerMod objects.
HLMdiag
(Package: HLMdiag) :
Diagnostic tools for hierarchical (multilevel) linear models
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.
This function is used to iteratively delete groups corresponding to the levels of a hierarchical linear model. It uses lmer() to fit the models for each deleted case (i.e. uses brute force). To investigate numerous levels of the model, the function will need to be called multiple times, specifying the group (level) of interest each time.
Separate linear models are fit via lm similar to lmList, however, adjust_lmList can handle models where a factor takes only one level within a group. In this case, the formula is updated eliminating the offending factors from the formula for that group as the effect is absorbed into the intercept.
This function calculates least squares (LS) residuals found by fitting separate LS regression models to each case. For examples see the documentation for HLMresid.
These functions calculate measures of the change in the covariance matrices for the fixed effects based on the deletetion of an observation, or group of observations, for a hierarchical linear model fit using lmer.
providing 
.