期刊名称：Journal of Data Analysis and Information Processing
印刷版ISSN：2327-7211
电子版ISSN：2327-7203
出版年度：2015
卷号：03
期号：03
页码：87-101
DOI：10.4236/jdaip.2015.33010
语种：English
出版社：Scientific Research Publishing
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.
关键词：Correlation Coefficient;Robustness;Type I Error Rate;Test Power;Non-Normality;Simulation
