Abstract #301175

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JSM 2002 Abstract #301175
Activity Number: 79
Type: Contributed
Date/Time: Monday, August 12, 2002 : 8:30 AM to 10:20 AM
Sponsor: Biometrics Section*
Abstract - #301175
Title: Effect of Informative Censoring on Survival Analysis
Author(s): Chin-Yu Lin*+ and Ramin Arani and Xinwei Jia
Affiliation(s): National Health Research Institutes and Johnson & Johnson Pharmaceutical R&D and Janssen Research Foundation
Address: 128 Yen-Chiu-Yuan Road, Section 2, Taipei, International, 11529, Taiwan
Keywords: informative censoring ; survival analysis ; bias ; power
Abstract:

In clinical trials with time-to-event endpoint, we often assume that censoring and failure times are independent. However, inherent to sampling scheme or effectiveness of drugs, there are situations that censoring depends on event of interest. This clearly violates the independence assumption and may, in turn, result in a bias estimate of survival curve and inadequate power in hypothesis testing. To resolve this issue, one needs to incorporate the dependence structure of censoring and failure times in sample size estimation and data analysis. We will explore the impact of the informative censoring on estimation and hypothesis testing when failure and censoring times follow Gumbel bivariate exponential model or bivariate additive gamma model.

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Revised March 2002