Identifying causal relationships from observational data is not easy. Still, researchers are often interested in examining the effects of policy changes or other decisions. In those analyses, ...

A model selection criterion, called the IC Q statistic, is proposed for selecting the penalty parameters (Ibrahim, Zhu, and Tang, 2008, Journal of the American Statistical Association 103, 1648-1658).

We address the problem of selecting which variables should be included in the fixed and random components of logistic mixed effects models for correlated data. A fully Bayesian variable selection is ...

Central to the idea of variance components models is the idea of fixed and random effects. Each effect in a variance components model must be classified as either a fixed or a random effect. Fixed ...

The main focus of this course will be on linear mixed models. That is, linear models with fixed effects and random effects. Some topics we’ll discuss are: When would I want to use a random effect? How ...

PROC GLM versus PROC MIXED for Random Effects Analysis Other SAS procedures that can be used to analyze models with random effects include the MIXED and VARCOMP procedures. Note that, for these ...