JSM 2004 - Toronto

Abstract #301112

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Activity Number: 439
Type: Contributed
Date/Time: Thursday, August 12, 2004 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistics in Epidemiology
Abstract - #301112
Title: Mixture Survival Models for Multiply Censored Data with Multiple Outcomes
Author(s): Nong Shang*+
Companies: Centers for Disease Control and Prevention
Address: , Atlanta, GA, ,
Keywords: survival analysis ; mixture model ; log-rank test ; censoring
Abstract:

When applying a treatment to a population, such as in a clinical trial, there may be multiple outcomes at the end of study. For example, the treatment may have no effects to some patients, while has short-term effects as well as long-term effects to the other patients, resulting in a mixture of three groups of patients. The complex nature of the trials may also bring in all types of censoring. Linear mixture survival models are applied to estimate the proportions and the survival functions of all subpopulations. Log-rank based tests are proposed to compare different treatment arms for each of the proportions and the survival functions.

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