JSM 2005 Online Program

Abstract #304593

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:	74
Type:	Contributed
Date/Time:	Sunday, August 7, 2005 : 8:00 PM to 9:50 PM
Sponsor:	Biopharmaceutical Section
Abstract - #304593
Title:	A Pattern-mixture Model for Censored Binary Longitudinal Data
Author(s):	Yuting Zhang*+ and Brent J. Shelton
Companies:	MedFocus and University of Kentucky
Address:	5064 Coventry Park CT, Duluth, GA, 30096, United States
Keywords:	missing data ; EM algorithm ; transition model ; mixture model
Abstract:	A pattern-mixture model is proposed to deal with binary longitudinal data subject to right censoring. We extend the general mixture model, which jointly models interval-scaled longitudinal data with missing at random, to the censored repeated binary responses. With an assumption that the repeated measures are correlated through only the previous measurement, we adapted a transitional logistic regression model fitted to the distribution of repeated binary outcomes combined with a nonparametric form for the nonresponse process. The estimates are obtained by the method of the Expectation-Maximization (EM) algorithm with weights combined with the quasi-Newton method to maximize the complete data likelihood in the maximization steps. The appropriate test statistics are described. An example is given to illustrate the proposed model. Sensitivity analysis is performed to address the adequacy and validity of this approach.

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