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Statistical Methods in Medical Research, Vol. 10, No. 2, 101-116 (2001)
DOI: 10.1177/096228020101000203

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

Gillian M Raab

School of Mathematics and Statistics, Napier University, Edinburgh, UK

Tamiza Parpia

Pfizer Global Research and Development, Sandwich, Kent, UK

The analysis of marker data from HIV positive patients has been the motivation for many new developments in applied statistics. As well as reviewing these methods, this paper considers the extent to which programs to implement them are available in current software. Particular areas of development have been the joint modelling of markers and survival outcomes, non-linear random effects models that are of particular relevance for studying the efficacy of treatments and the use of Bayesian computational methods for inference from marker data. The package Win BUGS is recommended as being particularly well suited to the analysis of marker data.


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Statistical Methods in Medical Research, April 1, 2005; 14(2): 171 - 192.
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