Probabilistic Decision Modeling
Probabilistic Decision Modeling is a formal analytic framework within decision science that characterizes uncertainty in model inputs through probability distributions and propagates this uncertainty via stochastic simulation to quantify the confidence in cost-effectiveness decisions, distinguishing it from deterministic models by explicitly accounting for parameter and model uncertainty in incremental cost-effectiveness analysis.
320
Publications
18.7K
Citations
880
Authors
444
Institutions
Publications per year
2017–2026
71
320
Probabilistic Sensitivity Analysis Using Monte Carlo Simulation
Peter M. Doubilet, Colin B. Begg, Milton C. Weinstein et al. · Medical Decision Making · 1985 · 851 citations
Bayesian best-worst method: A probabilistic group decision making model
Majid Mohammadi, Jafar Rezaei · Omega · 2019 · 427 citations · Full text
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444
University of Oxford
Oxford, United Kingdom
12 h-index
20 publications
1.7K citations

University of York
York, United Kingdom
9 h-index
30 publications
1.9K citations
Harvard University
Cambridge, United States
7 h-index
19 publications
544 citations

University of Bristol
Bristol, United Kingdom
7 h-index
15 publications
512 citations
Stanford University
Stanford, United States
6 h-index
13 publications
432 citations
University of Sheffield
Sheffield, United Kingdom
5 h-index
16 publications
1K citations
Georgia Institute of Technology
Atlanta, United States
5 h-index
13 publications
226 citations
KU Leuven
Leuven, Belgium
5 h-index
12 publications
453 citations
1–8 of 444
MDM · 20 publications · 2.3K citations
17
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7 publications · 654 citations
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6 publications · 672 citations
6
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5 publications · 1.1K citations
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Repository · 4 publications · 141 citations
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