- Input Uncertainty: Create distributions to represent uncertainty related to specific inputs.
- PSA Analysis: Sample a set input values from distributions, then run the model using those samples. Repeat this many times to generate a large set of results representing a wide range or parameter combinations.
- PSA Interpretation: Examine the set of results to assess confidence in the base case model conclusions. Some individual model calculations within the PSA will confirm your conclusions – the higher the percentage, the more confidence we have.
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