Survival data are described as interval censored when the failure time is not measured exactly but is known only to have occurred within a defined interval. In this paper, we describe and assess three methods for calculating pointwise confidence intervals for the non-parametric survivor function estimated from interval-censored data: the first based on the full information matrix, the second a modification of this approach involving deletion of rows and columns of the information matrix corresponding to zero estimates prior to inversion and the third based on likelihood ratio inference. In a simulation study the likelihood ratio method gave the most accurate confidence intervals with coverage consistently close to the nominal level of 95 per cent. Copyright © 2004 John Wiley & Sons, Ltd.
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