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Biostatistics 2:1-12 (2001)
© 2001 Oxford University Press

Incorporating retrospective data into an analysis of time to illness

Andrew J Copas* and Vernon T Farewell

Department of Statistical Science, University College London, Gower Street, London, WC1E 6BT, UK andrew{at}stats.ucl.ac.uk

For studies of time to illness, the prospective cohort study is, in general, the method of choice. When the time of origin is known for all subjects, then a prevalent cohort study in which individuals are recruited at variable times after the start of the illness process is a suitable alternative. Often, when a prevalent cohort is being formed, data may also be available on individuals who are already ill but are alive. The incorporation of such data, which is practically appealing to many researchers, is discussed. The nature of the required assumptions and the need also to model the illness to death process are illustrated. Full likelihood and pseudolikelihood techniques are outlined and compared with each other and with the use of only prevalent cohort data in a small simulation study. An example based on an HIV seroconverter study is discussed for illustration. The full likelihood method is seen to be too complex for general application. The use of pseudolikelihoods is easier to implement. If there is reliable information on initiating event times and recruitment strategies are well defined, then the incorporation of retrospective data may be beneficial. In other situations, their incorporation is too problematic to be recommended.

Keywords: Maximum likelihood; Prevalent cohort study; Pseudolikelihood; Retrospective data; Survival analysis.


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