Improved methods for making inferences about multiple skipped correlations. Issue 16 (2nd November 2018)

• Record Type: Journal Article
• Authors: Wilcox, Rand R.; Rousselet, Guillaume A.; Pernet, Cyril R.
• Is Part Of: Journal of statistical computation and simulation. Volume 88:Issue 16(2018)
• Page Start: 3116
• Page End: 3131
• Publication Date: 2018-11-02
• Subjects: Tests of independence -- multivariate outliers -- projection methods -- Pearson's correlation -- Spearman's rho; Mathematical statistics -- Data processing -- Periodicals; Digital computer simulation -- Periodicals; 519.5028505
• DOI: 10.1080/00949655.2018.1501051
• Languages: English
• ISSNs: 0094-9655

Abstract

Abstract: 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.