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Comparing dependent robust correlations
Author(s) -
Wilcox Rand R.
Publication year - 2016
Publication title -
british journal of mathematical and statistical psychology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.157
H-Index - 51
eISSN - 2044-8317
pISSN - 0007-1102
DOI - 10.1111/bmsp.12069
Subject(s) - pearson product moment correlation coefficient , outlier , correlation , statistics , extant taxon , mathematics , correlation coefficient , spearman's rank correlation coefficient , econometrics , percentile , population , medicine , geometry , evolutionary biology , biology , environmental health
Let r 1 and r 2 be two dependent estimates of Pearson's correlation. There is a substantial literature on testing H 0 : ρ 1 = ρ 2 , the hypothesis that the population correlation coefficients are equal. However, it is well known that Pearson's correlation is not robust. Even a single outlier can have a substantial impact on Pearson's correlation, resulting in a misleading understanding about the strength of the association among the bulk of the points. A way of mitigating this concern is to use a correlation coefficient that guards against outliers, many of which have been proposed. But apparently there are no results on how to compare dependent robust correlation coefficients when there is heteroscedasicity. Extant results suggest that a basic percentile bootstrap will perform reasonably well. This paper reports simulation results indicating the extent to which this is true when using Spearman's rho, a Winsorized correlation or a skipped correlation.