In a recent paper, Gaugler and Akritas (unpublished manuscript) considered testing for no main effect in a two-factor mixed effects design when the traditional assumptions do not hold. Here we extend ...

Testing that random effects are zero is difficult, because the null hypothesis restricts the corresponding variance parameter to the edge of the feasible parameter space. In the context of generalized ...

When some model effects are random (that is, assumed to be sampled from a normal population of effects), you can specify these effects in the RANDOM statement in order to compute the expected values ...

In this post, we’ll discuss some of the differences between fixed and random effects models when applied to panel data — that is, data collected over time on the same unit of analysis — and how these ...

Mixed Effect Models and Hierarchical Models Mixed Effect Models and Hierarchical Models Course Topics This course will discuss what mixed models are, why they are called "mixed" models, what is a ...

Fixed and Random Effects 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 ...