Longitudinal models for AIDS marker data.

Important note: Information in this article was accurate in 1998. The state of the art may have changed since the publication date.

Longitudinal models for AIDS marker data.

Stat Methods Med Res. 1998 Mar;7(1):13-27. Unique Identifier : AIDSLINE MED/98194458
Boscardin WJ; Taylor JM; Law N; Department of Biostatistics, UCLA 90095-1772, USA.

Abstract: Over the past decade, researchers have put a great amount of effort 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 different patterns of change in the marker data. In this paper, we review the existing literature including our preferred models which involve mixed effects, stochastic terms and independent measurement error. Adding stochastic terms to standard mixed effects 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 process allows for a range of biologically plausible derivative tracking that encompasses both random trajectory and Brownian motion behaviour. We illustrate these modelling techniques on longitudinal CD4 and viral RNA data.

Keywords: *Acquired Immunodeficiency Syndrome/ETIOLOGY *Models, Biological
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