Sensitivity analysis, Monte Carlo risk analysis, and Bayesian uncertainty assessment

Greenland, S

HERO ID

631228

Reference Type

Journal Article

Year

2001

Language

English

PMID

11726013

HERO ID 631228
In Press No
Year 2001
Title Sensitivity analysis, Monte Carlo risk analysis, and Bayesian uncertainty assessment
Authors Greenland, S
Journal Risk Analysis
Volume 21
Issue 4
Page Numbers 579-583
Abstract Standard statistical methods understate the uncertainty one should attach to effect estimates obtained from observational data. Among the methods used to address this problem are sensitivity analysis, Monte Carlo risk analysis (MCRA), and Bayesian uncertainty assessment. Estimates from MCRAs have been presented as if they were valid frequentist or Bayesian results, but examples show that they need not be either in actual applications. It is concluded that both sensitivity analyses and MCRA should begin with the same type of prior specification effort as Bayesian analysis.
Doi 10.1111/0272-4332.214136
Pmid 11726013
Wosid CCC:000172060000002
Is Certified Translation No
Dupe Override No
Is Public Yes
Language Text English
Keyword Bayesian analysis; epidemiologic methods; Monte Carlo analysis; relative risk; risk assessment