Nonparametric and semiparametric regression estimation for length-biased survival data

Yu Shen (), Jing Ning () and Jing Qin ()
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Yu Shen: The University of Texas MD Anderson Cancer Center
Jing Ning: The University of Texas MD Anderson Cancer Center
Jing Qin: National Institute of Health

Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, 2017, vol. 23, issue 1, No 2, 3-24

Abstract: Abstract For the past several decades, nonparametric and semiparametric modeling for conventional right-censored survival data has been investigated intensively under a noninformative censoring mechanism. However, these methods may not be applicable for analyzing right-censored survival data that arise from prevalent cohorts when the failure times are subject to length-biased sampling. This review article is intended to provide a summary of some newly developed methods as well as established methods for analyzing length-biased data.

Keywords: Length-biased sampling; Estimating equation; Left truncation; Likelihood; Nonparametric estimator; Semiparametric models (search for similar items in EconPapers)
Date: 2017
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DOI: 10.1007/s10985-016-9367-y

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