Algorithms versus models for analyzing data that contain misclassification errors.
Espeland and Hui (1987, Biometrics 43, 1001-1012) propose a methodology for analysing epidemiologic data contaminated by misclassification. They explicate their algorithm by a data set concerning cervical cancer and circumcision. We reanalyse these data using a conditional independence assumption different from theirs, and reach radically different conclusions. Espeland and Hui's methodology is a form of correlation analysis. We propose an alternative methodology based on the logic of regression analysis.
Ekholm
A
A
Department of Statistics, University of Helsinki, Finland.
D000465:Algorithms; D002944:Circumcision, Male; D004812:Epidemiologic Methods; D005260:Female; D006801:Humans; D008297:Male; D015233:Models, Statistical; D011336:Probability; D002583:Uterine Cervical Neoplasms / Q000209:etiology*