A comparison of group sequential methods for binary longitudinal data

Abstract

Interim analyses are conducted to allow for early termination of the trial, for ethical as well as economical reasons. Here we consider interim analyses in repeated measurements studies where the measurements are binary. Two methods for analysing this kind of data are compared according to their operating characteristics. A subject-specific approach based on the logistic random-effects model is compared with the population-averaged approach based on the generalized estimating equations. The comparison is illustrated with simulations using a randomized clinical trial for toenail fungal infection.