Notes on Interval Estimation Under the AB/BA Design in Multicenter Trials With Binary Responses

Abstract

A multicenter trial is often applied to facilitate recruiting patients into a trial and enhance the generalizability of results to a population. Under a distribution-free random effects logistic regression model, we derive three asymptotic interval estimators and one exact interval estimator for the treatment effect when assuming no treatment-by-center interactions. We note that one may apply interval estimators published elsewhere to estimate the treatment effect based on the data from each center separately when there are treatment-by-center interactions. We employ Monte Carlo simulation to evaluate the performance of these interval estimators in a variety of situations. We have found that all interval estimators developed here can actually perform well with the coverage probability larger than or equal to the desired confidence level. We use the data taken from a multicenter trial comparing an active drug with a placebo on the electrocardiogram to illustrate the use of the interval estimators developed here.