Random Effects Misspecification and its Consequences for Prediction in
Generalized Linear Mixed Models
Random Effects Misspecification and its Consequences for Prediction in
Generalized Linear Mixed Models
When fitting generalized linear mixed models (GLMMs), one important decision to make relates to the choice of the random effects distribution. As the random effects are unobserved, misspecification of this distribution is a real possibility. In this article, we investigate the consequences of random effects misspecification for point prediction and …