JSM 2005 Online Program

Abstract #304771

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:	200
Type:	Contributed
Date/Time:	Monday, August 8, 2005 : 2:00 PM to 3:50 PM
Sponsor:	Biopharmaceutical Section
Abstract - #304771
Title:	BANOVA for Repeated Measurements of Binary Data: Exact Inference for Parallel Group Design
Author(s):	Dar Shong Hwang*+ and James S. Lee
Companies:	B.R.S.I. and Sankyo Pharma Development
Address:	11 Trinity Place, East Hanover, NJ, 07936, United States
Keywords:	correlated binary variables ; Generalized constant odds ratio ; Exact conditional distribution ; Generalized treatment effect ; Generalized interaction effect ; Parallel group design
Abstract:	Planned Parallel Group Design, having repeated binary measurements over time, occurs frequently in clinical trials. Current statistical methods tend to apply large sample approximation methodologies such as GEE, WLS methods. To lessen the concern of management and FDA, a model-free exact analysis is proposed. Hwang et al. (2004b) dealt with the parallel group design having two repeated time points analogous to the classical analysis of a two-factor repeated measurement design for normal distribution data (Winer 1971). This paper extends the result to the general three or more time points. Analogous to Zelen's test of interaction and Birch-Cox-Gart's test of treatment effect---assuming no interaction for independent binary data, metrics, or parameters representing "generalized" treatment by time interaction---"generalized" treatment effect assuming no generalized interaction or "generalized" constant odds ratio for correlated binary data are developed. Existence and optimality of exact inference procedures are demonstrated and actual distributions are derived.

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