Proportional mean residual life model for right-censored length-biased data

Kwun Chuen Gary Chan, Ying Qing Chen and Chong-Zhi Di

Biometrika, 2012, vol. 99, issue 4, 995-1000

Abstract: To study disease association with risk factors in epidemiologic studies, cross-sectional sampling is often more focused and less costly for recruiting study subjects who have already experienced initiating events. For time-to-event outcome, however, such a sampling strategy may be length biased. Coupled with censoring, analysis of length-biased data can be quite challenging, due to induced informative censoring in which the survival time and censoring time are correlated through a common backward recurrence time. We propose to use the proportional mean residual life model of Oakes & Dasu (Biometrika 77, 409--10, 1990) for analysis of censored length-biased survival data. Several nonstandard data structures, including censoring of onset time and cross-sectional data without follow-up, can also be handled by the proposed methodology. Copyright 2012, Oxford University Press.

Date: 2012
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