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A Simulation Based Comparison of Correlation Coefficients with Regard to Type I Error Rate and Power
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作者 Elif Tugran Mehmet Kocak +2 位作者 Hamit Mirtagioglu soner yigit Mehmet Mendes 《Journal of Data Analysis and Information Processing》 2015年第3期87-101,共15页
In this simulation study, five correlation coefficients, namely, Pearson, Spearman, Kendal Tau, Permutation-based, and Winsorized were compared in terms of Type I error rate and power under different scenarios where t... In this simulation study, five correlation coefficients, namely, Pearson, Spearman, Kendal Tau, Permutation-based, and Winsorized were compared in terms of Type I error rate and power under different scenarios where the underlying distributions of the variables of interest, sample sizes and correlation patterns were varied. Simulation results showed that the Type I error rate and power of Pearson correlation coefficient were negatively affected by the distribution shapes especially for small sample sizes, which was much more pronounced for Spearman Rank and Kendal Tau correlation coefficients especially when sample sizes were small. In general, Permutation-based and Winsorized correlation coefficients are more robust to distribution shapes and correlation patterns, regardless of sample size. In conclusion, when assumptions of Pearson correlation coefficient are not satisfied, Permutation-based and Winsorized correlation coefficients seem to be better alternatives. 展开更多
关键词 Correlation Coefficient ROBUSTNESS Type I Error Rate Test Power NON-NORMALITY SIMULATION
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