Copyright © 2007 Biometrika Trust
Articles |
A pseudolikelihood method for analyzing interval censored data
Department of Statistics, University of Michigan, Ann Arbor, Michigan 48109, U.S.A.
bodhi{at}umich.edu
moulib{at}umich.edu
Received for publication 1 June 2005.
Revision received 1 May 2006.
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Abstract |
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We introduce a method based on a pseudolikelihood ratio for estimating the distribution function of the survival time in a mixed-case interval censoring model. In a mixed-case model, an individual is observed a random number of times, and at each time it is recorded whether an event has happened or not. One seeks to estimate the distribution of time to event. We use a Poisson process as the basis of a likelihood function to construct a pseudolikelihood ratio statistic for testing the value of the distribution function at a fixed point, and show that this converges under the null hypothesis to a known limit distribution, that can be expressed as a functional of different convex minorants of a two-sided Brownian motion process with parabolic drift. Construction of confidence sets then proceeds by standard inversion. The computation of the confidence sets is simple, requiring the use of the pool-adjacent-violators algorithm or a standard isotonic regression algorithm. We also illustrate the superiority of the proposed method over competitors based on resampling techniques or on the limit distribution of the maximum pseudolikelihood estimator, through simulation studies, and illustrate the different methods on a dataset involving time to HIV seroconversion in a group of haemophiliacs.
Key Words: greatest convex minorant • Haemophilia data • mixed-case interval censoring • panel count data • pseudolikelihood