Interest often centres on the comparison of failure time distributions based on interval-censored failure time data such as in the work by Finkelstein, in which she proposed a score test under continuous proportional hazards model. In this article, we consider a different situation in which the underlying failure time is a discrete variable or the observed times correspond with a discrete scale. To compare failure time distributions in these situations, we propose a non-parametric test, a generalization of the usual logrank test for right-censored failure time data. Simulation results indicate that the test performs satisfactorily.
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Several non-parametric test procedures have been proposed for incomplete survival data: interval-censored failure time data. However, most of them have unknown asymptotic properties with heuristically derived and/or complicated variance estimation. This article presents a class of generalized log-rank tests for this type of survival data and establishes their asymptotics. The methods are evaluated using simulation studies and illustrated by a set of real data from a cancer study. Copyright 2005 Board of the Foundation of the Scandinavian Journal of Statistics..
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