This Article Full Text (PDF) References Alert me when this article is cited Alert me if a correction is posted Services Email this article to a friend Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Add to Saved Citations Download to citation manager Request Permissions Request Reprints Add to My Marked Citations Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Citing Articles via Scopus Google Scholar Articles by Wang, Y.-G. Articles by Tan, S.-B. Search for Related Content PubMed PubMed Citation Articles by Wang, Y.-G. Articles by Tan, S.-B. Social Bookmarking                         What's this?

Bayesian designs with frequentist and Bayesian error rate considerations

Department of Statistics and Applied Probability, National University of Singapore, Singapore, you-gan.wang{at}csiro.au

Denis Heng-Yan Leung

School of Economics and Social Sciences, Singapore Management University, Singapore

Ming Li

Mathematical Sciences Institute, Australian National University, ACT, Australia

Say-Beng Tan

Division of Clinical Trials and Epidemiological Sciences, National Cancer Centre, Singapore

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.

Statistical Methods in Medical Research, Vol. 14, No. 5, 445-456 (2005)
DOI: 10.1191/0962280205sm410oa


CiteULike    Complore    Connotea    Del.icio.us    Digg    Reddit    Technorati    Twitter    What's this?

This article has been cited by other articles:

				J J. Lee and D. D Liu A predictive probability design for phase II cancer clinical trials Clinical Trials, April 1, 2008; 5(2): 93 - 106. [Abstract] [PDF]