Uncertainty analysis: An example of its application to estimating a survey proportion

Anne M. Jurek, George Maldonado, Sander Greenland, Timothy R. Church

Research output: Contribution to journalReview articlepeer-review

9 Scopus citations

Abstract

Uncertainty analysis is a method, established in engineering and policy analysis but relatively new to epidemiology, for the quantitative assessment of biases in the results of epidemiological studies. Each uncertainty analysis is situation specific, but usually involves four main steps: (1) specify the target parameter of interest and an equation for its estimator; (2) specify the equation for random and bias effects on the estimator; (3) specify prior probability distributions for the bias parameters; and (4) use Monte-Carlo or analytic techniques to propagate the uncertainty about the bias parameters through the equation, to obtain an approximate posterior probability distribution for the parameter of interest. A basic example is presented illustrating uncertainty analyses for four proportions estimated from a survey of the epidemiological literature.

Original languageEnglish (US)
Pages (from-to)650-654
Number of pages5
JournalJournal of epidemiology and community health
Volume61
Issue number7
DOIs
StatePublished - Jul 2007

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