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
Probabilistic Sensitivity Analysis Using Monte Carlo Simulation: A Practical Approach
β 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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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
## Abstract Probabilistic sensitivity analysis (PSA) is required to account for uncertainty in costβeffectiveness 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