Sequential monitoring of clinical trials with correlated responses

Stephen J. Gange, David L. DeMets

Research output: Contribution to journalArticle

Abstract

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.

Original languageEnglish (US)
Pages (from-to)157-167
Number of pages11
JournalBiometrika
Volume83
Issue number1
DOIs
StatePublished - Jan 1 1996

Keywords

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

ASJC Scopus subject areas

  • Statistics and Probability
  • Mathematics(all)
  • Agricultural and Biological Sciences (miscellaneous)
  • Agricultural and Biological Sciences(all)
  • Statistics, Probability and Uncertainty
  • Applied Mathematics

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