title: Proportional mean residual life model for right-censored length-biased data.
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 (Biometrika77, 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.
authors.affiliation: Department of Biostatistics, University of Washington, Seattle, Washington 98195, U.S.A. , kcgchan@u.washington.edu.
authors.forename: Kwun Chuen Gary
authors.initials: KC
authors.lastname: Chan
authors.forename: Ying Qing
authors.initials: YQ
authors.lastname: Chen
authors.forename: Chong-Zhi
authors.initials: CZ
authors.lastname: Di
keywords: Biased sampling; Bivariate survival data; Proportional hazards model; Renewal process