Nearly exact sample size calculation for powerful non‐randomized tests for differences between binomial proportions |
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| Authors: | Stefan Wellek |
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| Affiliation: | Department of Biostatistics, CIMH Mannheim/University of Heidelberg, D‐68159 Mannheim, Germany and Department of Medical Biostatistics, Epidemiology & Informatics, Johannes Gutenberg‐University, Mainz, Germany |
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| Abstract: | In the case of two independent samples, it turns out that among the procedures taken in consideration, BOSCHLOO'S technique of raising the nominal level in the standard conditional test as far as admissible performs best in terms of power against almost all alternatives. The computational burden entailed in exact sample size calculation is comparatively modest for both the uniformly most powerful unbiased randomized and the conservative non‐randomized version of the exact Fisher‐type test. Computing these values yields a pair of bounds enclosing the exact sample size required for the Boschloo test, and it seems reasonable to replace the exact value with the middle of the corresponding interval. Comparisons between these mid‐N estimates and the fully exact sample sizes lead to the conclusion that the extra computational effort required for obtaining the latter is mostly dispensable. This holds also true in the case of paired binary data (McNemar setting). In the latter, the level‐corrected score test turns out to be almost as powerful as the randomized uniformly most powerful unbiased test and should be preferred to the McNemar–Boschloo test. The mid‐N rule provides a fairly tight upper bound to the exact sample size for the score test for paired proportions. |
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| Keywords: | binomial two‐sample problem Boschloo's approach exact non‐conditional test McNemar setting nuisance parameter maximized p‐value score statistic |
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