Whitehead, John and Valdés-Márquez, Elsa and Johnson, Patrick and Graham, Gordon (2008) Bayesian sample size for exploratory clinical trials incorporating historical data. Statistics in Medicine, 27 (13). pp. 2307-2327.Full text not available from this repository.
This paper presents a simple Bayesian approach to sample size determination in clinical trials. It is required that the trial should be large enough to ensure that the data collected will provide convincing evidence, either that an experimental treatment is better than a control, or that it fails to improve upon control by some clinically relevant difference. The method resembles standard frequentist formulations of the problem, and indeed in certain circumstances involving “non-informative” prior information it leads to identical answers. In particular, unlike many Bayesian approaches to sample size determination, use is made of an alternative hypothesis that an experimental treatment is better than a control treatment by some specified magnitude. The approach is introduced in the context of testing whether a single stream of binary observations are consistent with a given success rate p0. Next the case of comparing two independent streams of normally distributed responses is considered, first under the assumption that their common variance is known and then for unknown variance. Finally, the more general situation in which a large sample is to be collected and analysed according to the asymptotic properties of the score statistic is explored.
|Journal or Publication Title:||Statistics in Medicine|
|Uncontrolled Keywords:||Bayesian methods ; clinical trial ; phase II trial ; proof-of-concept study ; sample size ; score statistic|
|Subjects:||Q Science > QA Mathematics|
|Departments:||Faculty of Science and Technology > Mathematics and Statistics|
|Deposited On:||25 May 2012 14:06|
|Last Modified:||09 Oct 2013 14:49|
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