For stratified 2 × 2 tables, standard approximate confidence limits can perform poorly from a strict frequentist perspective, even for moderate-sized samples, yet they are routinely used. In this paper, I show how to use importance sampling to compute highly accurate limits in reasonable time. The methodology is very general and simple to implement, and orders of magnitude are faster than existing alternatives.
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