Testing the significance of a correlation with nonnormal data: comparison of Pearson, Spearman, transformation, and resampling approaches.

@article{Bishara2012TestingTS,
  title={Testing the significance of a correlation with nonnormal data: comparison of Pearson, Spearman, transformation, and resampling approaches.},
  author={Anthony J Bishara and James B. Hittner},
  journal={Psychological methods},
  year={2012},
  volume={17 3},
  pages={399-417}
}
It is well known that when data are nonnormally 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
Recent Discussions
This paper has been referenced on Twitter 1 time over the past 90 days. VIEW TWEETS

From This Paper

Figures, tables, results, connections, and topics extracted from this paper.
38 Extracted Citations
51 Extracted References
Similar Papers

Citing Papers

Publications influenced by this paper.
Showing 1-10 of 38 extracted citations

Referenced Papers

Publications referenced by this paper.
Showing 1-10 of 51 references

Bootstrapping correlation coefficients using univariate and bivariate sampling

  • W. Lee, J. L. Rodgers
  • Psychological Methods
  • 1998
Highly Influential
4 Excerpts

Permutation test is not distributionfree : Testing H 0 :   0

  • A. Hayes
  • Psychological Methods
  • 1996
Highly Influential
9 Excerpts

Inheritance of properties of normal and non - normal distributions after transformation of scores to ranks

  • D. W. Zimmerman, B. D. Zumbo
  • Psicológica
  • 2011

The future of psychology practice and science

  • J. H. Bray
  • Amer - ican Psychologist
  • 2010
1 Excerpt

Robustness of Pearson correlation

  • P. Good
  • InterStat
  • 2009
2 Excerpts

Similar Papers

Loading similar papers…