What does probabilistic sensitivity analysis quantify?

What does probabilistic sensitivity analysis quantify?

• A. Parameter uncertainty across probability distributions.
• B. The effect of changing the WTP threshold.
• C. The average effect across all patients.
• D. Only structural uncertainty.

Answer: (A)

Probabilistic sensitivity analysis quantifies how uncertainty in the model’s inputs affects the results. By assigning probability distributions to uncertain parameters (like costs, effects, and probabilities) and repeatedly sampling from those distributions, you get a distribution of possible outcomes rather than a single point estimate. This shows how likely different results are and helps identify which parameters most influence the conclusions. It’s not about changing the willingness-to-pay threshold (that’s a threshold or scenario analysis), nor merely reporting an average effect across patients; its main purpose is to propagate parameter uncertainty through the analysis.

Probabilistic sensitivity analysis quantifies how uncertainty in the model’s inputs affects the results. By assigning probability distributions to uncertain parameters (like costs, effects, and probabilities) and repeatedly sampling from those distributions, you get a distribution of possible outcomes rather than a single point estimate. This shows how likely different results are and helps identify which parameters most influence the conclusions. It’s not about changing the willingness-to-pay threshold (that’s a threshold or scenario analysis), nor merely reporting an average effect across patients; its main purpose is to propagate parameter uncertainty through the analysis.