Generalized Linear and Nonlinear Models for Correlated Data: Theory and Applications Using SAS

7Additional Topics and Applications

7.1 Mixed models with non-Gaussian random effects

7.2 Pharmacokinetic applications

7.3 Joint modeling of longitudinal data and survival data

In this chapter, we consider four additional applications in which we apply some of the techniques described in previous chapters as well as a technique described by Nelson et. al. (2006) for fitting mixed-effects models with non-Gaussian random effects. We start in §7.1 by considering how one can use NLMIXED to fit mixed-effects models to correlated data assuming non-Gaussian random effects. This occurs, for example, in applications where one wishes to estimate the incidence rate of some event over time assuming the rate varies from subject to subject according to a gamma ...