Events and Meetings of Italian Statistical Society, Advances in Latent Variables - Methods, Models and Applications

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Ignoring the matching variables in cohort studies - when is it valid, and why?
Arvid Sjölander

Last modified: 2013-06-16

Abstract


In observational studies of the effect of an exposure on an outcome, the exposure-outcome association is usually confounded by other causes of the outcome. One common method to increase efficiency is to match the study on potential confounders. Matched case-control studies are relatively common and well covered by the literature. Matched cohort studies are less common but increasingly recommended. It is commonly asserted that it is valid to ignore the matching variables, in the analysis of matched cohort data. In this paper we provide analyses delineating the scope and limits of this assertion. We show that ignoring the matching variables in cohort studies produces a certain population causal effect. We discuss why the argument does not carry over to effect estimation in matched case-control studies although it does carry over to null-hypothesis testing. We also show how it does not extend to matched cohort studies when one adjusts for additional confounders.

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