title: Uncertainty analysis: an example of its application to estimating a survey proportion.
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.
authors.affiliation: Department of Pediatrics, University of Minnesota, Mayo Mail Code 715, 420 Delaware St SE, Minneapolis, MN 55455, USA. jure0007@umn.edu
authors.forename: Anne M
authors.initials: AM
authors.lastname: Jurek
authors.forename: George
authors.initials: G
authors.lastname: Maldonado
authors.forename: Sander
authors.initials: S
authors.lastname: Greenland
authors.forename: Timothy R
authors.initials: TR
authors.lastname: Church
mesh_terms: D015982:Bias; D009010:Monte Carlo Method; D035501:Uncertainty; D014481:United States