title: Unbiased vs. conservative estimators of etiological fractions: examples of misclassification from studies of occupational lung cancer.
abstract: Theoretical studies emphasize the importance of making unbiased etiological fraction estimates. In empirical works, however, the published estimates are usually conservative. The purpose of the present report is to study, empirically, the numerical magnitude of such conservative biases. Examples from the literature on occupational exposure and lung cancer are reported. It is demonstrated that conservative bias may decrease a numerical estimate by more than a factor 10 and that decreases by a factor 2 or 3 are not unusual. It is concluded that it is important, in future review studies, to pay attention to the magnitude of the conservative biases in the published empirical estimates and to put most emphasis on the least biased estimates in the review process.
authors.affiliation: Department of Occupational Medicine, Danish National Institute of Occupational Health, Copenhagen.
authors.forename: O
authors.initials: O
authors.lastname: Olsen
mesh_terms: D001194:Asbestos / Q000009:adverse effects; D015982:Bias; D016022:Case-Control Studies; D015984:Causality; D003625:Data Collection / Q000379:methods; D003627:Data Interpretation, Statistical; D003718:Denmark / Q000453:epidemiology; D006801:Humans; D015994:Incidence; D008175:Lung Neoplasms / Q000453:epidemiology* / Q000209:etiology; D016273:Occupational Exposure / Q000009:adverse effects / Q000145:classification / Q000706:statistics & numerical data*; D015995:Prevalence; D012307:Risk Factors; D018401:Sample Size
chemical_list: D001194:Asbestos