Assess Overall Parameter Uncertainty with PSA

Probabilistic Sensitivity Analysis (PSA) –
Analyze how parameter uncertainty affects model results & conclusions

• 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.

Click here for detailed product documentation on PSA.