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

Publication Type:

Journal Article


Biometrika, Volume 99, Issue 4, p.995-1000 (2012)


2012, August 2013, Center-Authored Paper, Public Health Sciences Division, Vaccine and Infectious Disease Division


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.