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Activity Number: 250
Type: Contributed
Date/Time: Tuesday, August 8, 2006 : 8:30 AM to 10:20 AM
Sponsor: Section on Statistics in Epidemiology
Abstract - #305828
Title: Estimating Equation Approach for Regression Analysis of Interval-Censored Failure Time Data
Author(s): HeeJeong Lim*+ and Xingqiu Zhao and Jianguo Sun
Companies: California State University, Fullerton and McMaster University and University of Missouri-Columbia
Address: Department of Mathematics, Fullerton, CA, 92834,
Keywords: estimating equations ; interval-censoring ; proportional hazards models ; regression analysis
Abstract:

This article discusses statistical inference for the proportional hazards model when there exists interval-censoring on both survival time of interest and covariates (J. Roy. Statist. Soc. B 34, (1972) 187; Encyclopedia of Biostatistics. Wiley, New York, 1998, pp.2090-2095). In particular, we consider situations where observations on the survival time are doubly censored and covariates are interval-censored. For inference about regression parameters, a general estimating equation approach is proposed. The proposed estimate of the parameter is a generalization of the maximum partial-likelihood estimate for right-censored failure time data with known or exactly observed covariates (Statistical Analysis of Failure Time Data. Wiley, New York, 1980). The asymptotic properties of the proposed estimate are established and its finite sample properties are investigated through a simulation study.


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