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Proportional mean residual life model for right-censored length-biased data
Biometrika (2012)
  • Gary KWUN CHUEN Chan, University of Washington
  • Ying Qing Chen, Fred Hutchinson Cancer Research Center
  • Chongzhi Di, Fred Hutchinson Cancer Research Center
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 the so-called “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 and Dasu (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 be handled by the proposed methodology.

Publication Date
Winter 2012
Citation Information
Gary KWUN CHUEN Chan, Ying Qing Chen and Chongzhi Di. "Proportional mean residual life model for right-censored length-biased data" Biometrika Vol. 99 Iss. 4 (2012)
Available at: http://works.bepress.com/di/14/