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March 16, 2011

Statistical Association and Causation: Contributions of Different Types of Evidence

Author Affiliations

Author Affiliations: Charles E. Schmidt College of Medicine, Florida Atlantic University, Nova Southeastern University, and University of Miami Miller School of Medicine, Boca Raton, Florida (Dr Hennekens); and Department of Biostatistics and Informatics, University of Wisconsin School of Medicine, Madison (Dr DeMets).

JAMA. 2011;305(11):1134-1135. doi:10.1001/jama.2011.322

Advances in medical knowledge proceed on several fronts, optimally simultaneously. Each discipline provides unique, relevant, and complementary information to a totality of evidence. When the totality of evidence is sufficient, health care professionals can make the most rational decisions for individual patients and policy makers can make the most rational decisions for the health of the general public.1 When the totality of evidence is incomplete, it is appropriate to remain uncertain.2 Nonetheless, health care professionals and policy makers are always faced with decision making. Although medical researchers are likely to be familiar with these concepts, this commentary is primarily for clinicians and policy makers to increase their knowledge and understanding of the unique contributions of different types of evidence to the conclusion of a valid statistical association as well as the need to evaluate the totality of evidence to judge causality.

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