A number of new study designs have appeared in which the exposure distribution of a case series is compared to an exposure distribution representing a complete theoretical population or distribution. These designs include the case-genotype study, the case-cross-over study, and the case-specular study. This paper describes a unified likelihood-based approach to the analysis of such studies, and discusses extensions of these methods when a control group is available. The approach clarifies certain assumptions implicit in the methods, and helps contrast these assumptions to those underlying ordinary case-control studies. There are several reasons to expect discrepancies between ordinary case-control estimates and case-distribution estimates; for example, case-distribution estimates can be more sensitive to exposure misclassification. Some discrepancies are illustrated in an application to case-specular data on wire codes and childhood cancer. Copyright © 1999 John Wiley & Sons, Ltd.
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