A Simulation Based Comparison of Correlation Coefficients with Regard to Type I Error Rate and Power

• 作者: Elif Tu?ran Hamit Mirtagio?lu Mehmet Kocak Mehmet Mendes Soner Yi?it
• 来源期刊: 数据分析和信息处理(英文)
• 学科: 医学
• 关键词: CORRELATION COEFFICIENT ROBUSTNESS Type I ERROR Rate Test POWER NON-NORMALITY Simulation
• 年，卷（期）: 2015,（3）
• 页码范围: 87-101
• 页数: 15页
• 分类号: R73

摘要

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.