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Probabilistic analysis of decision trees using Monte Carlo simulation.

G C Critchfield, K E Willard

    Medical Decision Making : an International Journal of the Society for Medical Decision Making
    |April 1, 1986
    PubMed
    Summary
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    This study introduces Monte Carlo simulation for decision tree uncertainty, providing exact confidence levels and sensitivity measures. These methods offer quantitative insights into decision model limitations for complex problems.

    Area of Science:

    • Decision Analysis
    • Computational Statistics
    • Medical Informatics

    Background:

    • Decision models often face uncertainty in probability and utility specifications.
    • Quantifying this uncertainty is crucial for robust decision-making.
    • Existing methods may not fully address specification uncertainty in complex models.