F-Test Alternatives to Fisher’s Exact Test and to the Chi-Square Test of Homogeneity in 2 × 2 Tables
John E. Overall, Robert R. Starbuck
Abstract
John E. Overall, Robert R. Starbuck
Abstract
A binomial model is proposed for testing the significance of differences in binary response probabilities in two independent treatment groups. Without correction for continuity, the binomial statistic is essentially equivalent to Fisher’s exact probability. With correction for continuity, the binomial statistic approaches Pearson’s chi-square. Due to mutual dependence of the binomial and F distributions on the beta distribution, a simple F statistic can be used for computation instead of the binomial.
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A binomial model is proposed for testing the significance of differences in binary response probabilities in two independent treatment groups. Without correction for continuity, the binomial statistic is essentially equivalent to Fisher’s exact probability. With correction for continuity, the binomial statistic approaches Pearson’s chi-square. Due to mutual dependence of the binomial and F distributions on the beta distribution, a simple F statistic can be used for computation instead of the binomial.
Key concepts: Pearson's chi-squared test, Mathematics, Chi-square test, Statistics, Binomial test, Exact test, Continuity correction, Binomial (polynomial)