A comparison of different matching designs in case-control studies: an empirical example using continuous exposures, continuous confounders and incidence of myocardial infarction.

The paper presents a case-control study involving a disease, exposures and several continuous confounders. The relative efficiency and validity of a fully matched design is compared with random sampling of controls. We test a viable option of a partially matched design when inability to match all study subjects on all confounders occurs. The degree of bias in the odds ratios introduced by the different designs and by the different analytic models is assessed in comparison with the estimates obtained from a total cohort, from which both cases and controls were selected. Matched designs and analytic strategies are also evaluated in terms of the variances of the odds ratios. The results indicate that matching on continuous variables may lead to a more precise estimate of odds ratio than statistical control of confounding in unmatched designs. Partial selection of controls by matching may be a useful strategy when complete matching cannot be achieved; in practice, partial matching achieves most of the benefits of full matching.