ArticleMedical decision making : an international journal of the Society for Medical Decision Making2015
Computing Expected Value of Partial Sample Information from Probabilistic Sensitivity Analysis Using Linear Regression Metamodeling.
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 25 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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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
25 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Clinical and cost-effectiveness of detailed anomaly ultrasound screening in the first trimester: a mixed-methods study.Health technology assessment (Winchester, England) · 2025Pooled it
- Microsimulation Estimates of Decision Uncertainty and Value of Information Are Biased but Consistent.Medical decision making : an international journal of the Society for Medical Decision Making · 2025Article
- Making Drug Approval Decisions in the Face of Uncertainty: Cumulative Evidence versus Value of Information.Medical decision making : an international journal of the Society for Medical Decision Making · 2024Article
- Value of Information for Clinical Trial Design: The Importance of Considering All Relevant Comparators.PharmacoEconomics · 2024Article
- Closed-Form Solution of the Unit Normal Loss Integral in 2 Dimensions, with Application in Value-of-Information Analysis.Medical decision making : an international journal of the Society for Medical Decision Making · 2023Article
- Metamodeling for Policy Simulations with Multivariate Outcomes.Medical decision making : an international journal of the Society for Medical Decision Making · 2022Article
- Emerging Therapies for COVID-19: The Value of Information From More Clinical Trials.Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research · 2022Article
- Calculating Expected Value of Sample Information Adjusting for Imperfect Implementation.Medical decision making : an international journal of the Society for Medical Decision Making · 2022Article
- Personalization of Medical Treatment Decisions: Simplifying Complex Models while Maintaining Patient Health Outcomes.Medical decision making : an international journal of the Society for Medical Decision Making · 2022Article
- Expected Value of Sample Information to Guide the Design of Group Sequential Clinical Trials.Medical decision making : an international journal of the Society for Medical Decision Making · 2022Article
- Multilevel and Quasi Monte Carlo Methods for the Calculation of the Expected Value of Partial Perfect Information.Medical decision making : an international journal of the Society for Medical Decision Making · 2022Article
- Is further research on adult pneumococcal vaccine uptake improvement programs worthwhile? Α value of information analysis.Vaccine · 2021Article
- Comparison of Decision Modeling Approaches for Health Technology and Policy Evaluation.Medical decision making : an international journal of the Society for Medical Decision Making · 2021Article
- Cost-effectiveness of teduglutide in pediatric patients with short bowel syndrome: Markov modeling using traditional cost-effectiveness criteria.The American journal of clinical nutrition · 2021Article
- Prioritizing Additional Data Collection to Reduce Decision Uncertainty in the HIV/AIDS Response in 6 US Cities: A Value of Information Analysis.Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research · 2020Article
- Computing the Expected Value of Sample Information Efficiently: Practical Guidance and Recommendations for Four Model-Based Methods.Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research · 2020Article
- Calculating the Expected Value of Sample Information in Practice: Considerations from 3 Case Studies.Medical decision making : an international journal of the Society for Medical Decision Making · 2020Article
- Cost-effectiveness of teduglutide in adult patients with short bowel syndrome: Markov modeling using traditional cost-effectiveness criteria.The American journal of clinical nutrition · 2020Article
- The Curve of Optimal Sample Size (COSS): A Graphical Representation of the Optimal Sample Size from a Value of Information Analysis.PharmacoEconomics · 2019Article
- A Gaussian Approximation Approach for Value of Information Analysis.Medical decision making : an international journal of the Society for Medical Decision Making · 2018Article
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3 authors.
Funding
Abstract
Decision makers often desire both guidance on the most cost-effective interventions given current knowledge and also the value of collecting additional information to improve the decisions made (i.e., from value of information [VOI] analysis). Unfortunately, VOI analysis remains underused due to the conceptual, mathematical, and computational challenges of implementing Bayesian decision-theoretic approaches in models of sufficient complexity for real-world decision making. In this study, we propose a novel practical approach for conducting VOI analysis using a combination of probabilistic sensitivity analysis, linear regression metamodeling, and unit normal loss integral function--a parametric approach to VOI analysis. We adopt a linear approximation and leverage a fundamental assumption of VOI analysis, which requires that all sources of prior uncertainties be accurately specified. We provide examples of the approach and show that the assumptions we make do not induce substantial bias but greatly reduce the computational time needed to perform VOI analysis. Our approach avoids the need to analytically solve or approximate joint Bayesian updating, requires only one set of probabilistic sensitivity analysis simulations, and can be applied in models with correlated input parameters.
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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.