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The counter-matching design for sampling from risk sets is presented in which each sampled risk set includes the failure and a random sample of controls from ‘sampling strata’ defined by exposure information available for all cohort subjects. Asymptotic relative efficiency comparisons indicate that this type of sampling has superior efficiency to simple nested case-control sampling in situations of practical interest. A simple extension of the method is given which allows for nonrepresentative sampling of failures. Analysis of data from counter-matched studies may be performed using standard conditional logistic likelihood software which allows for an ‘offset’ in the model.