JSM 2005 Online Program

Abstract #303305

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:	31
Type:	Contributed
Date/Time:	Sunday, August 7, 2005 : 2:00 PM to 3:50 PM
Sponsor:	Biometrics Section
Abstract - #303305
Title:	The ANCOVA Model for the Binary Response Variable
Author(s):	Yi-Ting Hwang*+
Companies:	National Taipei University
Address:	67 Sec 3 Ming Sheng E Rd, Taipei, 104, Taiwan
Keywords:	ANCOVA model ; binary data ; chi-square test ; likelihood ratio test ; simulations
Abstract:	Many clinical trials are conducted to develop a new drug or a treatment comparing to an existing drug or placebo. Usually, a new drug has to be proved to be more effective than the existing drug or placebo before practicing the new treatment or marketing the new drug. The effectiveness of a new drug can be measured as success or failure. The problem is to examine the association for a 2x2 contingence table. Many tests, a two independent sample Z test for the proportion, the Pearson chi-square test, and the likelihood ratio test, can be used. These tests have power when the sample size is relatively large. However, in recent years, demands for a reliable small-area statistic have increased. From the previous result, the sample size can be reduced by introducing the covariate into the experimental design by n*=n/RE, where n is the total sample size and RE is the relative efficiency of a design that controls for the covariate to the simpler design. A test adapting the regression estimator is proposed. Simulations are performed to evaluate the power and desired level of the new proposed method, which has descent power under a relative small sample.

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