Running Head : CORRELATION WITH NON-NORMAL DATA 1 Testing the Significance of a Correlation with Non-normal Data : Comparison of Pearson , Spearman , Transformation , and Resampling Approaches

@inproceedings{Bishara2012RunningH,
  title={Running Head : CORRELATION WITH NON-NORMAL DATA 1 Testing the Significance of a Correlation with Non-normal Data : Comparison of Pearson , Spearman , Transformation , and Resampling Approaches},
  author={Anthony J Bishara and James B. Hittner},
  year={2012}
}
It is well known that when data are non-normally distributed, a test of the significance of Pearson's r may inflate Type I error rates and reduce power. Statistics textbooks and the simulation literature provide several alternatives to Pearson’s correlation. However, the relative performance of these alternatives has been unclear. Two simulation studies were conducted to compare 12 methods, including Pearson, Spearman's rank-order, transformation, and resampling approaches. With most sample… CONTINUE READING
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