Linear mixed models (LMMs) serve as a versatile statistical framework, combining fixed effects that capture the overall trends with random effects that account for variability across subjects, ...

It is traditionally assumed that the random effects in mixed models follow a multivariate normal distribution, making likelihood-based inferences more feasible theoretically and computationally.

We describe a generalized linear mixed model in which all random effects may evolve over time. Random effects have a discrete support and follow a first-order Markov chain. Constraints control the ...

Just as PROC GLM is the flagship procedure for fixed-effect linear models, the MIXED procedure is the flagship procedure for random- and mixed-effect linear models. PROC MIXED fits a variety of mixed ...

Keywords: Statistical analyses. Regression models. Post-earthquake ignitions. Data analyses. California. Ground shaking. Generalized linear mixed models. Goodness-of ...

Ask yourself the following questions. If you need some background, look up material on "mixed effects","hierarchical models" in wikipedia. What is a linear model? What is an additive effects model?