Abstract
In epidemiological studies there are numerous challenges to finding an appropriate experimental design for studying the relationship between an exposure and a disease. A number of designs for observational studies have been investigated; the cohort study and the standard case-control study are the primary types. The nested case-control study design combines features of both. In the nested case-control study some information is available for all cohort members and additional information is obtained using a case-control design based on incidence density sampling rather than cumulative prevalence sampling. To get higher efficiency, it is important to effectively use the information already available on cohort members when we choose the controls. The counter-matched design is one such method, which chooses the controls based on exposure status or a surrogate measure of the exposure. It has high efficiency to estimate the effect of the exposure or interaction between the exposure and another risk factor. Unfortunately, there are few examples of application of this design to real situations. To encourage use of the counter-matched design, we describe the basic concept and statistical methods underlying the method. Some examples are presented to illustrate how to implement the design. We also propose some extensions to provide a more flexible sampling design.
