JSM 2005 Online Program

Abstract #303543

This is the preliminary program for the 2005 Joint Statistical Meetings in Minneapolis, Minnesota. Currently included in this program is the "technical" program, schedule of invited, topic contributed, regular contributed and poster sessions; Continuing Education courses (August 7-10, 2005); and Committee and Business Meetings. This on-line program will be updated frequently to reflect the most current revisions.

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Activity Number:	447
Type:	Contributed
Date/Time:	Wednesday, August 10, 2005 : 2:00 PM to 3:50 PM
Sponsor:	General Methodology
Abstract - #303543
Title:	Semiparametric Transformation Models for Survival Data with a Cure Fraction
Author(s):	Donglin Zeng*+ and Guosheng Yin and Joseph G. Ibrahim
Companies:	University of North Carolina, Chapel Hill and The University of Texas M. D. Anderson Cancer Center and University of North Carolina, Chapel Hill
Address:	Department of Biostatistics, Chapel Hill, NC, 27516, United States
Keywords:	Cure Model ; Linear Transformation Model ; Semiparametric Efficiency
Abstract:	We propose a class of transformation models for survival data with a cure fraction. The class of transformation models is motivated by biologic considerations and includes {\em both} the proportional hazards and proportional odds cure models as two special cases. An efficient recursive algorithm is proposed to calculate the maximum likelihood estimators. Furthermore, the maximum likelihood estimators for the regression coefficients are shown to be consistent and asymptotically normal, and their asymptotic variances attain the semiparametric efficiency bound. Simulation studies are conducted to examine the finite sample properties of the proposed estimators and a real dataset is presented to illustrate the methodology.

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