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Performance of Pearson, Spearman, and Kendall Correlation Coefficients Under Bivariate Count Distributions

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Pearson's correlation test achieved the highest power even at small sample sizes when assessing correlations of 0.6 and 0.8.
Bivariate count distributions, including binomial and Poisson, were analyzed for type I error control and power performance.
Correlations were evaluated across varying sample sizes of 10, 20, 30, 50, and 100, maintaining a significance level of 0.05.
Findings indicate the significance of choosing appropriate correlation coefficients based on data distribution characteristics.

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Simulation results show correlations effectively control type I error, suggesting Pearson's method optimizes power.

Chumnaul et al. (2025) studied this question.

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