Estimation Following Adaptively Randomised Clinical Trials
SteveĀ Coad
School of Mathematical Sciences, Queen Mary, University of London, London, United Kingdom

Suppose that two treatments are being compared in a clinical trial in which response-adaptive randomisation is used. Upon termination of the trial, interest lies in estimating parameters of interest. Although the usual estimators will be approximately unbiased for trials with moderate to large numbers of patients, their biases may be appreciable for small to moderate-sized trials and the corresponding confidence intervals may also have coverage probabilities far from the nominal values. An adaptive two-parameter model is studied in which there is a parameter of interest and a nuisance parameter. Corrected confidence intervals based on the signed root transformation are constructed for the parameter of interest which have coverage probabilities close to the nominal values for trials with a small number of patients. The accuracy of the approximations is assessed by simulation for two examples.

Keywords: Approximately pivotal quantity; Maximum likelihood estimator; Response-adaptive randomisation; Signed root transformation

Biography: Steve Coad is a Reader in Statistics at Queen Mary, University of London, where he has worked since 2005, having previously held appointments at the Universities of Sussex, Michigan and Newcastle upon Tyne. He obtained his DPhil from the University of Oxford. He is currently an Associate Editor for Sequential Analysis and the Journal of Statistical Planning and Inference, and has been a Chartered Statistician since 1993 and a Chartered Mathematician since 1998. His research interests are mainly in the area of sequential design and analysis, with particular emphasis on estimation problems, asymptotic approximations and adaptive treatment allocation.