Estimating the quality-of-life-adjusted gap time distribution of successive events subject to censoring

Adin-Cristian Andrei and Susan Murray

Biometrika, 2006, vol. 93, issue 2, 343-355

Abstract: When treatment effects are studied in the context of successive or recurrent life events, separate analyses of the quality-of-life scores and of the inter-event, gap, times might lead to possibly contradictory conclusions. In an attempt to reconcile this, we propose a unitary and more comprehensive nonparametric analysis that combines the two separate analyses by introducing the quality-of-life-adjusted gap time concept. Inverse probability of censoring estimators of the quality-of-life-adjusted gap time joint and conditional distributions are proposed and are shown to be consistent and asymptotically normal. Simulations performed in a variety of scenarios indicate that the joint and conditional quality-of-life-adjusted gap time distribution estimators are virtually unbiased, with properly estimated standard errors and asymptotic normality features. An example from the International Breast Cancer Study Group Trial V illustrates the use of the proposed estimators. Copyright 2006, Oxford University Press.

Date: 2006
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