This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.

Abstract Details

Activity Number: 72
Type: Contributed
Date/Time: Sunday, August 1, 2010 : 4:00 PM to 5:50 PM
Sponsor: Biopharmaceutical Section
Abstract - #308442
Title: Inference on Treatment Effect Under a Density Ratio Model and Random Censoring
Author(s): Shan Jiang*+ and Dongsheng Tu
Companies: Queen's University and Queen's University
Address: Department of Mathematics and Statistics, Kingston, ON, K7L 3N6, Canada
Keywords: clinical trial ; censored data ; treatment effect ; empirical likelihood ; confidence interval ; simulation
Abstract:

Let T_1 and T_2 be the survival times of patients randomized to respectively two treatment groups. The probability P(T_1< T_2) may be used as a measure on the effect of treatments in a randomized clinical trial. In this paper, with potentially censored data observed and assuming that the density functions of the survival times satisfy a semiparametric density ratio model, we propose two estimates of this probability based on respectively likelihood of uncensored survival times and a weighted empirical likelihood. Associated confidence intervals are also derived based on asymptotic normality of the estimates and bootstrap resampling. The assessment on the goodness-of-fit of density ratio model is also discussed. The proposed inference procedures are evaluated by Monte-Carlo simulations and applied to analysis of data from a clinical trial on early breast cancer.


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