Nonparametric Analysis of Truncated Survival Data, with Application to AIDS

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Abstract
One source of data for the induction distribution of AIDS arises from persons infected by the AIDS virus from contaminated blood transfusions. Analyses of these data are complicated because the number of individuals infected by transfusion is unknown; information is available only for those who are infected and develop AIDS within a certain chronologic time interval. The statistical problem is one of making inferences about a stochastic process of infection and disease for which realizations are right truncated in chronologic time. By considering the process in reverse time, we transform the problem to one of analysing survival data that are left truncated in internal time. We develop nonparametric methods for estimating and comparing the identifiable aspects of the induction distributions of several groups.

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