Random effects models for HIV marker data: practical approaches with currently available software

The analysis of marker data from HIV positive patients has been the motivat ion for many. new developments in applied statistics. As well as reviewing these methods, this paper considers the extent to which programs to impleme nt them are available in current software. Particular areas of development hare been the joint modelling of markers and survival outcomes, non-linear random effects models that are of particular relevance for studying the eff icacy of treatments and the use of Bayesian computational methods for infer ence from marker data. The package WinBUGS is recommended as being particul arly well suited to the analysis of marker data.