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Deterministic Sensitivity Analysis/Evidence
Method evidence record

Deterministic Sensitivity Analysis

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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Source record

Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.

Deterministic Sensitivity Analysis — Systematic Parameter Variation for Model Robustness
Taxonomic method record · process-pipeline / simulation
  • 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
  • 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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Related methods

Generated from the method graph and shown as machine-suggested relations — no evidence claim is inferred.

See alsoMONTE-CARLO-SIMULATIONmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketStochastic Sensitivity Analysismachine-suggested · Relational suggestion, not evidence.

Evidence status

Sources recorded, not reviewed

Bibliographic sources are present. Claim-level evidence review has not been performed.

Sources

2 recorded citations, copied from the method source record.

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