Process / pipelineSimulation / optimization

Deterministic Sensitivity Analysis — Systematic Parameter Variation for Model Robustness

Deterministic Sensitivity Analysis (DSA) tests how model outputs change when individual or combined input parameters are varied across plausible ranges, one at a time or in structured combinations, without invoking probabilistic sampling. It is the standard approach in economic modeling, decision trees, and mathematical programming to identify which parameters drive conclusions and to demonstrate model robustness to regulators, reviewers, and stakeholders.

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Sources

  1. Saltelli, A., Tarantola, S., Campolongo, F., & Ratto, M. (2004). Sensitivity Analysis in Practice: A Guide to Assessing Scientific Models. John Wiley & Sons, Chichester. ISBN: 9780470870938
  2. Briggs, A., Sculpher, M., & Buxton, M. (1994). Uncertainty in the economic evaluation of health care technologies: the role of sensitivity analysis. Health Economics, 3(2), 95–104. DOI: 10.1002/hec.4730030206

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ScholarGateDeterministic Sensitivity Analysis (Deterministic Sensitivity Analysis — Systematic Parameter Variation for Model Robustness). Retrieved 2026-06-04 from https://scholargate.app/en/simulation/deterministic-sensitivity-analysis