Sample Size, Error Rates and Optimality Considerations for Phase II Clinical Trials
So far, most Phase II trials have been designed and analysed under a frequentist framework. Under this framework, a trial is designed so that the overall Type I and Type II errors of the trial are controlled at some desired levels. Recently, a number of articles have advocated the use of Bayesian designs in practice. Under a Bayesian framework, a trial is designed so that the trial stops when the posterior probability of treatment is within certain prespecified thresholds. In this article, we argue that trials under a Bayesian framework can also be designed to control frequentist error rates. We introduce a Bayesian version of Simon's well-known two-stage design to achieve this goal. We also consider two other errors, which are called Bayesian errors in this article because of their similarities to posterior probabilities. We show that our method can also control these Bayesian-type errors. We compare our method with other recent Bayesian designs in a numerical study and discuss implications of different designs on error rates. An example of a clinical trial for patients with nasopharyngeal carcinoma is used to illustrate differences of the different designs.
Applied Statistics | Economics
Statistical Methods in Medical Research
Wang, Y. G.; Leung, Denis H. Y.; Li, M.; and TAN, S. B..
Sample Size, Error Rates and Optimality Considerations for Phase II Clinical Trials. (2005). Statistical Methods in Medical Research. 14, (5), 445-456. Research Collection School Of Economics.
Available at: http://ink.library.smu.edu.sg/soe_research/418