Probabilistic sensitivity analysis is criticised for potentially introducing uncertainty itself because of the consideration of the distribution of the parameters. Are there ways of addressing this potential for additional uncertainty?
The distribution of parameters is inherent in the model, so not really 'uncertainty' that is introduced: it would be there naturally anyway in real life :)