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Abstract Details

Activity Number: 63
Type: Topic Contributed
Date/Time: Sunday, July 29, 2012 : 4:00 PM to 5:50 AM
Sponsor: ENAR
Abstract - #304287
Title: Empirical Likelihood for Additive Hazards Regression with Current Status Data
Author(s): Xuewen Lu*+ and Wanrong Liu and Lingxue Pan
Companies: University of Calgary and Hunan Normal University and Aspire Commodities, LP
Address: Department of Mathematics & Statistics, Calgary, AB, T2N 1N4, Canada
Keywords: Additive hazards regression ; Current status data ; Empirical likelihood ; Normal approximation ; B-spline

In this article, we investigate the empirical likelihood method for the additive hazards regression model with current status data. An empirical likelihood ratio for the vector of regression parameters is defined and its limiting distribution is shown to be a standard chi-squared distribution. The proposed inference procedure enables us to make empirical likelihood based inference for the regression parameters. Finite sample performance of the proposed method is assessed in simulation studies to compare with that of a normal approximation based method. A real data example is used for illustration.

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