Assurance for clinical trial design with normally distributed outcomes: eliciting uncertainty about variances
Abstract
The assurance method is growing in popularity in clinical trial planning. The method involves eliciting a prior distribution for the treatment effect, and then calculating the probability that a proposed trial will produce a `successful' outcome. For normally distributed observations, uncertainty about the variance of the normal distribution also needs to be accounted for, but there is little guidance in the literature on how to elicit a distribution for a variance parameter. We present a simple elicitation method, and illustrate how the elicited distribution is incorporated within an assurance calculation. We also consider multi-stage trials, where a decision to proceed with a larger trial will follow from the outcome of a smaller trial; we illustrate the role of the elicted distribution in assessing the information provided by a proposed smaller trial. Free software is available for implementing our methods.
Keywords
Cite
@article{arxiv.1702.00978,
title = {Assurance for clinical trial design with normally distributed outcomes: eliciting uncertainty about variances},
author = {Ziyad A. Alhussain and Jeremy E. Oakley},
journal= {arXiv preprint arXiv:1702.00978},
year = {2019}
}
Comments
The previous version of this paper had the title "Eliciting judgements about uncertain population means and variances". The elicitation methods in this paper are unchanged from the previous version. The motivation for the methods has changed, and the scope of the paper has been widened, to show the application of the elicitation methods within the assurance method for clinical trial planning