JSM 2005 - Toronto

Abstract #304749

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Legend: = Applied Session, = Theme Session, = Presenter
Activity Number: 66
Type: Contributed
Date/Time: Sunday, August 7, 2005 : 4:00 PM to 5:50 PM
Sponsor: ENAR
Abstract - #304749
Title: A Weighted Empirical Estimation of a Distribution Function with Interval-censored and Truncated Observations
Author(s): Hsiao-Chuan Tien*+ and Pai-Lien Chen
Companies: University of North Carolina, Chapel Hill and Family Health International
Address: Dept of Biostatistics, Chapel Hill, NC, 27599, United States
Keywords: interval censored ; truncated
Abstract:

The need to estimate a distribution function F using interval-censored and truncated observations arises in many medical applications. The nonparametric maximum likelihood estimator (NPMLE) based on characterizations on subsets of the original support of F proposed by Turnbull (1976) has been widely cited in the statistical literature. However, in some cases, these subsets are so restricted that the resulting estimators provide little information about the distribution function. To better describe the distribution function F, we propose a new characterization that none of the subset of censored intervals would have zero probability. According to this new characterization, a weighted empirical estimator for the distribution function is developed. We conducted simulations to investigate the behavior of the estimator and used a clinical study to illustrate the use of the method.

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