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Abstract
Better Ways to Improve Standards in Brain-Behavior Correlation Analysis
Highlights
Rousselet and Pernet (2012) demonstrate that outliers can skew Pearson correlation. They claim that this leads to widespread statistical errors by selecting and re-analyzing a cohort of published studies
Because their selection criteria are based on the authors’ belief that a study used misleading statistics, their study represents an example of “double dipping” (Kriegeskorte et al, 2009). The strong claims they make about the literature are circular and unjustified by their data. Their purely statistical approach does not consider the biological context of what observations constitute outliers
They propose that the skipped correlation (Wilcox, 2005) is an appropriate alternative to the Pearson correlation that is robust to outliers
Summary
Rousselet and Pernet (2012) demonstrate that outliers can skew Pearson correlation. They claim that this leads to widespread statistical errors by selecting and re-analyzing a cohort of published studies. Rousselet and Pernet (2012) demonstrate that outliers can skew Pearson correlation. Their purely statistical approach does not consider the biological context of what observations constitute outliers. This test lacks statistical power to detect true relationships (Figure 1A) and is highly prone to false positives (Figure 1B).
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