Causal diagrams and the logic of matched case-control studies
Eyal Shahar,1 Doron J Shahar,2
1Division of Epidemiology and Biostatistics, Mel and Enid Zuckerman College of Public Health, 2Departments of Physics and Mathematics, College of Science, The University of Arizona, Tucson, AZ, USA
Abstract: It is tempting to assume that confounding bias is eliminated by choosing controls that are identical to the cases on the matched confounder(s). We used causal diagrams to explain why such matching not only fails to remove confounding bias, but also adds colliding bias, and why both types of bias are removed by conditioning on the matched confounder(s). As in some publications, we trace the logic of matching to a possible tradeoff between effort and variance, not between effort and bias. Lastly, we explain why the analysis of a matched case-control study – regardless of the method of matching – is not conceptually different from that of an unmatched study.
Keywords: causal diagrams, directed acyclic graphs, case-control study, matching, confounding bias, colliding bias, variance
Corrigendum for this paper has been published
This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution - Non Commercial (unported, v3.0) License. By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms.