The survival function NPMLE for combined right-censored and length-biased right-censored failure time data: properties and applications

被引：0
|
作者：
McVittie, James H. [1 ]
Wolfson, David B. [2 ]
Stephens, David A. [2 ]
机构：
[1] Univ Regina, Dept Math & Stat, Regina, SK S4S 0A2, Canada
[2] McGill Univ, Dept Math & Stat, Montreal, PQ H3A 0G4, Canada
来源：
INTERNATIONAL JOURNAL OF BIOSTATISTICS | 2024年
关键词：
censoring; cohort; length-bias; nonparametric; survival; truncation; EMPIRICAL DISTRIBUTIONS; PREVALENT COHORT; STATIONARITY; CURVE;
D O I：
10.1515/ijb-2023-0121
中图分类号：
Q [生物科学];
学科分类号：
07 ; 0710 ; 09 ;
摘要：
Many cohort studies in survival analysis have imbedded in them subcohorts consisting of incident cases and prevalent cases. Instead of analysing the data from the incident and prevalent cohorts alone, there are surely advantages to combining the data from these two subcohorts. In this paper, we discuss a survival function nonparametric maximum likelihood estimator (NPMLE) using both length-biased right-censored prevalent cohort data and right-censored incident cohort data. We establish the asymptotic properties of the survival function NPMLE and utilize the NPMLE to estimate the distribution for time spent in a Montreal area hospital.
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页数：21
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