JSM 2005 Online Program

Abstract #302969

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:	51
Type:	Invited
Date/Time:	Sunday, August 7, 2005 : 4:00 PM to 5:50 PM
Sponsor:	Biometrics Section
Abstract - #302969
Title:	Sample-Size Formula for Clustered Survival Data Using Weighted Log-rank Statistics
Author(s):	Ronald Gangnon*+ and Michael Kosorok
Companies:	University of Wisconsin, Madison and University of Wisconsin, Madison
Address:	207 WARF Office Building, Madison, WI, 53726,
Keywords:	Clustered data ; Log-rank statistic ; Local alternatives ; Martingale residuals ; Paired data ; Proportional hazards
Abstract:	We present a simple sample-size formula for weighted log-rank statistics applied to clustered survival data with variable cluster sizes and arbitrary treatment assignments within clusters. This formula is based on the asymptotic normality of weighted log-rank statistics under certain local alternatives in the clustered data context. We also provide consistent variance estimators. The derived sample-size formula reduces to Schoenfeld's (1983) formula for cases of no clustering or independence within clusters. Simulation results verify control of the Type I error and accuracy of the sample-size formula. Use of the sample-size formula in an event-driven clinical trial design is illustrated using data from the Early Treatment Diabetic Retinopathy Study.

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