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To capture the dependences of a disease on several risk factors, a challengeis to combine model-based estimation with evidence-based arguments. Standardcase-control methods allow estimation of the dependences of a rare disease onseveral regressors via logistic regressions. For case-control studies, thesampling design leads to samples from two different populations and for the setof regressors in every logistic regression, these samples are then mixed andtaken as given observations. But, it is the differences in independencestructures of regressors for cases and for controls that can improve logisticregression estimates and guide us to the important feature dependences that arespecific to the diseased. A case-control study on laryngeal cancer is used asillustration.

Case-control studies for rare diseases: improved estimation of several risks and of feature dependences