Robust Microsimulation
Robust Microsimulation combines individual-level (micro) simulation with systematic uncertainty analysis — typically probabilistic sensitivity analysis — to generate outputs that are robust to parameter uncertainty, model structure assumptions, and input variability. It is widely used in health technology assessment, public policy, and social science to produce credible, decision-relevant predictions.
Source record
Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.
- O'Brien, B. J., & Briggs, A. H. (2002). Analysis of uncertainty in health care cost-effectiveness studies: an introduction to statistical issues and methods. Statistical Methods in Medical Research, 11(6), 455-468. · DOI 10.1191/0962280202sm304ra
- Caro, J. J., Briggs, A. H., Siebert, U., & Burgess, K. A. (2012). Modeling good research practices — overview: a report of the ISPOR-SMDM Modeling Good Research Practices Task Force-1. Medical Decision Making, 32(5), 667-677. · DOI 10.1177/0272989X12454577
Curated claims
Claims persisted in the evidence ledger, each with its own assessment.
This view does not invent a claim assessment when the ledger has none.
Related methods
Generated from the method graph and shown as machine-suggested relations — no evidence claim is inferred.