Ren, S., Minton, J., Whyte, S. et al. (2 more authors) (2018) A New Approach for Sampling Ordered Parameters in Probabilistic Sensitivity Analysis. PharmacoEconomics, 36 (3). pp. 341-347. ISSN 1170-7690
Abstract
Background
Probabilistic sensitivity analysis (PSA) in cost-effectiveness analysis involves sampling a large number of realisations of an economic model. For some parameters, we may be uncertain around the true mean values of the variables, but the ordering of the values is known. Typical sampling approaches lack either statistical or clinical validity. For example, sampling using a common number generator results in extreme dependence and independent sampling can lead to realisations with incorrect ordering.
Methods
We propose a new sampling approach for ordered parameters, the Difference Method approach, which samples the parameters of interest via a difference parameter. If the parameters of interest are bounded, it involves transforming the variables so that they are unbounded and then sampling via the difference parameter. We have provided an Excel workbook to implement the method. The proposed approach is illustrated with an example sampling ordered parameters for utility and cost.
Results
The DM approach has a number of advantages when comparing with the typical approaches used in practice. The DM approach generates PSA samples which have similar summary statistics as the given values in our examples whilst maintaining the constraint that one value was greater than another. The method also implies plausible positive correlation between the two ordered variables.
Conclusions
Both clinical and statistical validity should be checked when producing PSA samples. The DM approach should be considered as a solution to potential problems in generating PSA samples for ordered parameters.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © The Author(s) 2017. Open Access This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Medicine, Dentistry and Health (Sheffield) > School of Health and Related Research (Sheffield) > ScHARR - Sheffield Centre for Health and Related Research |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 19 Oct 2017 14:47 |
Last Modified: | 15 Dec 2023 16:46 |
Status: | Published |
Publisher: | Springer International Publishing |
Refereed: | Yes |
Identification Number: | 10.1007/s40273-017-0584-3 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:122547 |