Assurance for clinical trial design with normally distributed outcomes: Eliciting uncertainty about variances. (14th June 2020)

• Record Type: Journal Article
• Authors: Alhussain, Ziyad A.; Oakley, Jeremy E.
• Is Part Of: Pharmaceutical statistics. Volume 19:Number 6(2020)
• Page Start: 827
• Page End: 839
• Publication Date: 2020-06-14
• Subjects: assurance -- expert judgement -- prior elicitation -- variance elicitation; Pharmacy -- Statistical methods -- Periodicals; Pharmacy -- Statistics -- Periodicals; 615.10727
• DOI: 10.1002/pst.2040
• Languages: English
• ISSNs: 1539-1604

Abstract

Summary: 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 elicited distribution in assessing the information provided by a proposed smaller trial. Free software is available for implementing our methods.