ArticleMedical decision making : an international journal of the Society for Medical Decision Making2015
Estimating the Expected Value of Sample Information Using the Probabilistic Sensitivity Analysis Sample: A Fast, Nonparametric Regression-Based Method.
Article in Medical decision making : an international journal of the Society for Medical Decision Making, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 60 papers, 3 of them syntheses that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
60 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Thromboprophylaxis during pregnancy and the puerperium: a systematic review and economic evaluation to estimate the value of future research.Health technology assessment (Winchester, England) · 2024Pooled it
- Defining the optimum strategy for identifying adults and children with coeliac disease: systematic review and economic modelling.Health technology assessment (Winchester, England) · 2022Pooled it
- Cost-Effectiveness of Treatments for the Management of Bone Metastases: A Systematic Literature Review.PharmacoEconomics · 2018Pooled it
- General-Purpose Methods for Simulating Survival Data for Expected Value of Sample Information Calculations.Medical decision making : an international journal of the Society for Medical Decision Making · 2023Trial
- Antimicrobial-impregnated central venous catheters for preventing neonatal bloodstream infection: the PREVAIL RCT.Health technology assessment (Winchester, England) · 2020Trial
- Cost-effectiveness of strategies preventing late-onset infection in preterm infants.Archives of disease in childhood · 2020Trial
- A Pragmatic Bayesian Adaptive Trial Design Based on the Value of Information: The Value-Driven Adaptive Design.Medical decision making : an international journal of the Society for Medical Decision Making · 2026Article
- Developing shortcut algorithms for value-based pricing of pharmaceuticals.Health economics review · 2026Article
- Study protocol - the Australian National Child hearing Health Outcomes Registry (ANCHOR): collecting and connecting national data into a child deafness Learning Health System.BMC health services research · 2026Article
- Global sensitivity analysis of integrated assessment models with multivariate outputs.Risk analysis : an official publication of the Society for Risk Analysis · 2025Article
- Assessing the value for money, from a policy maker perspective, of 24 randomised controlled trial designs for an online weight maintenance guided self-help intervention: an expected value of sample information analysis.International journal of obesity (2005) · 2025Article
- Value-adaptive clinical trial designs for efficient delivery of publicly funded trials - a discussion of methods, case studies, opportunities and challenges.BMC medical research methodology · 2025Article
- Optimising error rates in programmes of pilot and definitive trials using Bayesian statistical decision theory.Statistical methods in medical research · 2025Article
- Article
- A Nonparametric Approach for Estimating the Effective Sample Size in Gaussian Approximation of Expected Value of Sample Information.Medical decision making : an international journal of the Society for Medical Decision Making · 2025Article
- Accurate EVSI Estimation for Nonlinear Models Using the Gaussian Approximation Method.Medical decision making : an international journal of the Society for Medical Decision Making · 2024Article
- Calculating the Expected Net Benefit of Sampling for Survival Data: A Tutorial and Case Study.Medical decision making : an international journal of the Society for Medical Decision Making · 2024Article
- Rapid Assessment of the Need for Evidence: Applying the Principles of Value of Information to Research Prioritisation.PharmacoEconomics · 2024Article
- Value of Information for Clinical Trial Design: The Importance of Considering All Relevant Comparators.PharmacoEconomics · 2024Article
- Health economic evaluation of strategies to eliminate gambiense human African trypanosomiasis in the Mandoul disease focus of Chad.PLoS neglected tropical diseases · 2023Article
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Abstract
Health economic decision-analytic models are used to estimate the expected net benefits of competing decision options. The true values of the input parameters of such models are rarely known with certainty, and it is often useful to quantify the value to the decision maker of reducing uncertainty through collecting new data. In the context of a particular decision problem, the value of a proposed research design can be quantified by its expected value of sample information (EVSI). EVSI is commonly estimated via a 2-level Monte Carlo procedure in which plausible data sets are generated in an outer loop, and then, conditional on these, the parameters of the decision model are updated via Bayes rule and sampled in an inner loop. At each iteration of the inner loop, the decision model is evaluated. This is computationally demanding and may be difficult if the posterior distribution of the model parameters conditional on sampled data is hard to sample from. We describe a fast nonparametric regression-based method for estimating per-patient EVSI that requires only the probabilistic sensitivity analysis sample (i.e., the set of samples drawn from the joint distribution of the parameters and the corresponding net benefits). The method avoids the need to sample from the posterior distributions of the parameters and avoids the need to rerun the model. The only requirement is that sample data sets can be generated. The method is applicable with a model of any complexity and with any specification of model parameter distribution. We demonstrate in a case study the superior efficiency of the regression method over the 2-level Monte Carlo method.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.