Statistical Evaluation of Exposure Assessment Strategies

Abstract

Abstract It is well known that exposure measurement error or misclassification can bias an epidemiologic risk assessment. Accordingly, it is useful to have methods of assessing the degree of error in exposure assessments. This paper proposes statistical evaluation techniques for two types of exposure assessment strategies: categorization of exposure and estimation of actual personal exposure levels (with particular attention to the latter). Categorization of exposure is generally done in one of the two ways: ordinal but nonquantitative grouping or quantitative exposure intervals. Estimation of actual exposure levels is most often done in the form of job-by-year exposure matrices and somewhat less often by exposure prediction models. The nature of uncertainty inherent with each of these approaches is described. Quantitative estimates of the magnitude of error in an exposure assessment are possible when exposure matrices or prediction models are employed. Three types of statistical approaches are explored f...