What do I make of your latinorumc Sensitivity auditing of mathematical modelling

Abstract

Sensitivity analysis, mandated by existing guidelines as a good practice to use in conjunction to mathematical modelling, is as such insufficient to ensure quality in the treatment of uncertainty of science for policy. If one accepts that policy-related science calls for an extension of the traditional internal, peer review-based methods of quality assurance to higher levels of supervision, where extended participation and explicit value judgments are necessary, then by the same token sensitivity analysis must extend beyond the technical exploration of the space of uncertain assumptions when the inference being sought via mathematical modelling is subject to relevant uncertainties and stakes. We thus provide seven rules to extend the use of sensitivity analysis (or how to apportion uncertainty in model-based inference among input factors) in a process of sensitivity auditing of models used in a policy context. Each rule will be illustrated by examples.

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