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Probabilistic Sensitivity Analysis Using Monte Carlo Simulation: A Practical Approach

✍ Scribed by Doubilet, P.; Begg, C. B.; Weinstein, M. C.; Braun, P.; McNeil, B. J.


Book ID
126768579
Publisher
SAGE Publications
Year
1985
Tongue
English
Weight
1007 KB
Volume
5
Category
Article
ISSN
0272-989X

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πŸ“œ SIMILAR VOLUMES


Probabilistic Sensitivity Analysis Using
✍ Doubilet, P.; Begg, C. B.; Weinstein, M. C.; Braun, P.; McNeil, B. J. πŸ“‚ Article πŸ“… 1985 πŸ› SAGE Publications 🌐 English βš– 1007 KB

The data for medical decision analyses are often unreliable. Traditional sensitivity analysisvarying one or more probability or utility estimates from baseline values to see if the optimal strategy changes -is cumbersome if more than two values are allowed to vary concurrently. This paper describes

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✍ Yu Wang; Zijun Cao; Siu-Kui Au πŸ“‚ Article πŸ“… 2010 πŸ› Elsevier Science 🌐 English βš– 511 KB

Monte Carlo Simulation (MCS) method has been widely used in probabilistic analysis of slope stability, and it provides a robust and simple way to assess failure probability. However, MCS method does not offer insight into the relative contributions of various uncertainties (e.g., inherent spatial va

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✍ Anthony O'Hagan; Matt Stevenson; Jason Madan πŸ“‚ Article πŸ“… 2007 πŸ› John Wiley and Sons 🌐 English βš– 185 KB

## Abstract Probabilistic sensitivity analysis (PSA) is required to account for uncertainty in cost‐effectiveness calculations arising from health economic models. The simplest way to perform PSA in practice is by Monte Carlo methods, which involves running the model many times using randomly sampl