Bias Correction in Group Sequential Analysis with Correlated Data

This paper focuses on the bias of the group sequential estimate of treatment effect for correlated data using the generalized estimating equation (GEE) method and the Lan and DeMets alpha-spending function. Linear and logistic regressions are used to examine (a) the magnitude of the bias of a sequential estimate with correlated data; (b) the influence of the true correlation structure on bias. A bias-corrected sequential estimate is proposed using a Brownian motion approximation and numerical simulation. Logistic regression is used to illustrate and to assess the performance of the proposed method.