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Nonparametric Estimation of the Bivariate Survival Function with Truncated Data by Mark J. van der Laan is a Mathematics article available to read on EtoBox.

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Randomly left or right truncated observations occur when one is concerned with estimation of the distribution of time between two events and when one only observes the time if one of the two events falls in a fixed time-window, so that longer survivial times have higher probability to be part of the sample than short survival times. In important AIDS-applications the time between seroconversion and AIDS is only observed if the person did not die before the start of the time-window. Hence, here the time of interest is truncated if another related time-variable is truncated. This problem is a special case of estimation of the bivariate survival function based on truncation by a bivariate truncation time, the problem covered in this paper; in the AIDS-application one component of the bivariate truncation timevector is alway zero. In this application the bivariate survival function is of interest itself in order to study the relation between time till AIDS and time between AIDS and death. We provide a quick algorithm for computation of the NPMLE. In particular, it is shown that the NPMLE is explicit for the special case when one of the truncation times is zero, as in the aids-applicati

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Author

Mark J. van der Laan

Publisher

Elsevier Science; Elsevier ; Elsevier Inc.; Elsevier BV (ISSN 0047-259X)

Published

1996

Language

EN

Field

Mathematics (Physical Sciences)