ArticlePharmacoEconomics2018
A New Approach for Sampling Ordered Parameters in Probabilistic Sensitivity Analysis.
Article in PharmacoEconomics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 2 of them syntheses that pooled it.
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Who cites it
5 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Indocyanine Green Fluorescence Imaging for Colorectal Surgery: A Health Technology Assessment.Ontario health technology assessment series · 2025Pooled it
- Clinical and cost-effectiveness of left ventricular assist devices as destination therapy for advanced heart failure: systematic review and economic evaluation.Health technology assessment (Winchester, England) · 2024Pooled it
- Simplified Methods for Modelling Dependent Parameters in Health Economic Evaluations: A Tutorial.Applied health economics and health policy · 2024Article
- The Difference Method Approach for Sampling Order Constrained Parameters: An Improved Implementation and Important Limitations.PharmacoEconomics · 2024Article
- Cost-effectiveness of long-term clinical management of BRCA pathogenic variant carriers.Genetics in medicine : official journal of the American College of Medical Genetics · 2020Article
Corrections and comments
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Authors and funding
5 authors.
Funding
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Abstract
backgroundProbabilistic 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.
methodsWe propose a new sampling approach for ordered parameters, the difference method (DM) 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 a Microsoft Excel workbook to implement the method. The proposed approach is illustrated with an example sampling ordered parameters for utility and cost.
resultsThe DM approach has a number of advantages when comparing with the typical approaches used in practice. It generates PSA samples that have similar summary statistics as the given values in our examples, while maintaining the constraint that one value was greater than another. The method also implies plausible positive correlation between the two ordered variables.
conclusionsBoth 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.
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