Nonparametric sequential monitoring of longitudinal trials

Abstract

This paper considers the sequential monitoring of multi-armed longitudinal clinical trials. We describe an approach that is relatively simple and accessible. Sequential ranks are used to form partial sum statistics, yielding processes that have independent increments, and hence can be approximated by Brownian motions. Three monitoring procedures are proposed. The first two are asymptotic, continuous analogues of the well-known Pocock and O'Brien-Fleming group sequential procedures, whereas the third procedure is exact. Performance of the procedures is assessed using Monte Carlo simulations. Data from an orthodontic clinical trial is used to illustrate the proposed methods, for the comparison of three treatment groups.