Longitudinal models for AIDS marker data

Over the past decade, researchers have put a great amount of e#ort into developing suitable models for the analysis of longitudinal CD4 data and other markers of AIDS progression. These models must be general enough to allow for di#erent patterns of change in the marker data. In this paper, we review the existing literature including our preferred models whichinvolve mixed e#ects, stochastic terms and independent measurement error. Adding stochastic terms to standard mixed e#ects models gives an interpretable and parsimonious method for generalizing the covariance structure of the measurement error and short-term variability. We focus on univariate and bivariate models with Integrated Ornstein-Uhlenbeck #IOU# stochastic terms. The IOU # Address for correspondence: JeremyM.G.Taylor, Department of Biostatistics, UCLA, Los Angeles, California 90095-1772, USA. 1 process allows for a range of biologically plausible derivative tracking that encompasses both random trajectory a...