Improved methods for making inferences about multiple skipped correlations

Rand Wilcox, Guillaume A. Rousselet, Cyril R Pernet

Research output: Contribution to journalArticlepeer-review


A skipped correlation has the advantage of dealing with outliers in a manner that takes into account the overall structure of the data cloud. For p-variate data, p≥2, there is an extant method for testing the hypothesis of a zero correlation for each pair of variables that is designed to control the probability of one or more Type I errors. And there are methods for the related situation where the focus is on the association between a dependent variable and p explanatory variables. However, there are limitations and several concerns with extant techniques. The paper describes alternative approaches that deal with these issues
Original languageEnglish
JournalJournal of Statistical Computation and Simulation
Early online date23 Jul 2018
Publication statusE-pub ahead of print - 23 Jul 2018


  • Tests of independence
  • multivariate outliers
  • projection methods
  • Pearson's correlation
  • Spearman's rho

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