Model Building in Nonlinear Mixed Effects Models

Nonlinear mixed effects models involve both fixed effects and random effects. Model building for nonlinear mixed effects is the process of determining the characteristics of both the fixed and the random effects so as to give an adequate but parsimonious model. We describe procedures based on information criterion statistics for comparing different structures of the random effects component. These include procedures for determining which parameters in the model should be mixed effects and which should be purely fixed effects, as well as procedures for modeling the dependence of parameters on cluster-specific covariates. These methods are illustrated using the nonlinear mixed effects methods and classes for S-plus and using data sets from a laboratory pharmacokinetic study and from a pharmacokinetics clinical study.