Robust Correlation Analyses: False Positive and Power Validation Using a New Open Source Matlab Toolbox

By Cyril R. Pernet, Rand R. Wilcox, Guillaume A. Rousselet. Front. Psychology, 2012

550 citations recorded by the source corpus.

Pearson’s correlation measures the strength of the association between two variables. The technique is, however, restricted to linear associations and is overly sensitive to outliers. Indeed, a single outlier can result in a highly inaccurate summary of the data. Yet, it remains the most commonly used measure of association in psychology research. Here we describe a free Matlab(R) based toolbox (http://sourceforge.net/projects/robustcorrtool/) that computes robust measures of association between two or more random variables: the percentage-bend correlation and skipped-correlations. After illustrating how to use the toolbox, we show that robust methods, where outliers are down weighted or removed and accounted for in significance testing, provide better estimates of the true association with accurate false positive control and without loss of power. The different correlation methods were tested with normal data and normal data contaminated with marginal or bivariate outliers. We report estimates of effect size, false positive rate and power, and advise on which technique to use depending on the data at hand.

Subfields: Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/7cb52413bdb0d39ff4fcbedb12b9ad7e9e85d2ef

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Individual differences among deep neural network models (2020, background): “001; (Pernet et al., 2013)), indicating that network layers that separate categories better do exhibit stronger individual differences.”
Temporal expectation based on the duration variability modulates alpha oscillations during working memory retention (2022, methodology): “To further confirm the correlation effect while taking the potential influence from outliers into account in significance testing, we additionally performed a robust correlation analysis (Pernet et al., 2013) and the permutation statistics as implemented in Fieldtrip (Maris and Oostenveld, 2007) wit”