For multilevel analyses (e.g., linear mixed models), researchers are often interested in pooling, interpreting, and testing both fixed effects and random effects. For multiply imputed data, the results of one's analyses need to be pooled across the imputed data sets. Current software cannot easily pool variance estimates. Also, current software packages typically conduct significance testing using Wald-type tests that are inappropriate for testing variance estimates. Likelihood ratio testing is a more flexible approach, as it can be used to compare models that differ in both fixed and random effects. This program fits two user-specified models in PROC MIXED, pools the estimates from those models across imputed data sets (including variance components), and implements a pooled likelihood ratio test that is appropriate for multiply imputed data.
