Measuring uncertainty in complex decision analysis models

Giovanni Parmigiani

Research output: Contribution to journalArticlepeer-review

22 Scopus citations


Prediction models used in support of clinical and health policy decision making often need to consider the course of a disease over an extended period of time, and draw evidence from a broad knowledge base, including epidemiologic cohort and case control studies, randomized clinical trials, expert opinions, and more. This paper is a brief introduction to these decision models, their relation to Bayesian decision theory, and the tools typically used to describe the uncertainties involved. Concepts are illustrated throughout via a simplified tutorial.

Original languageEnglish (US)
Pages (from-to)513-537
Number of pages25
JournalStatistical Methods in Medical Research
Issue number6
StatePublished - Dec 2002

ASJC Scopus subject areas

  • Epidemiology
  • Health Information Management
  • General Nursing


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