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Biometrika 1996 83(1):157-167; doi:10.1093/biomet/83.1.157
© 1996 by Biometrika Trust
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Sequential monitoring of clinical trials with correlated responses

STEPHEN J. GANGE and DAVID L. DEMETS

Department of Epidemiology, The Johns Hopkins School of Hygiene and Public Health Baltimore, Maryland 21205, U.S.A.
Department of Biostatistics, University of Wisconsin-Madison Madison, Wisconsin 53792, U.S.A.

This paper demonstrates how the alpha-spending method of Lan & DeMets (1983) can be applied to the generalised estimating equations regression model for correlated data proposed by Liang & Zeger (1986). Under large-sample conditions, the sequential regression parameters are shown to have an independent increments structure, conditional on the amount of Type I error allocated at each interim analysis. We propose and evaluate surrogates for the information fraction, which determines this allocation of Type I error. Data from the Early Treatment Diabetic Retinopathy Study are used to illustrate the proposed methods for ordered polytomous outcomes. Some key words: Alpha-spending method; Generalised estimating equations; Group sequential testing; Ordinal regression.

Key Words: Alpha-spending method • Generalised estimating equations • Group sequential testing • Ordinal regression


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