Alhussain, Z. and Oakley, J. orcid.org/0000-0002-9860-4093 (2020) Assurance for clinical trial design with normally distributed outcomes: eliciting uncertainty about variances. Pharmaceutical Statistics, 19 (6). pp. 827-839. ISSN 1539-1604
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 elicited distribution in assessing the information provided by a proposed smaller trial. Free software is available for implementing our methods.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2020 The Authors. Pharmaceutical Statistics published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution License, (http://creativecommons.org/licenses/by/4.0/) which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
Keywords: | assurance; prior elicitation; expert judgement; variance elicitation |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Science (Sheffield) > School of Mathematics and Statistics (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 19 May 2020 09:41 |
Last Modified: | 13 Jul 2021 15:51 |
Status: | Published |
Publisher: | Wiley |
Refereed: | Yes |
Identification Number: | 10.1002/pst.2040 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:160946 |