Interval estimation for response adaptive clinical trials

In this paper we examine a new method for constructing confidence intervals for the difference of success probabilities to analyze dependent data from response adaptive designs with binary responses. Specifically we investigate the feasibility of the Jeffreys-Perks procedure for interval estimation. Simulation results are derived to demonstrate the performance of the Jeffreys-Perks procedure compared with the profile likelihood method. It is found that both asymptotic methods perform well for small sample sizes despite being approximate procedures.