Improved methods for making inferences about multiple skipped correlations

被引：9
|
作者：
Wilcox, Rand R. [1 ]
Rousselet, Guillaume A. [2 ]
Pernet, Cyril R. [3 ]
机构：
[1] Univ Southern Calif, Dept Psychol, SGM 1061, Los Angeles, CA 90089 USA
[2] Univ Glasgow, Coll Med Vet & Life, Inst Neurosci & Psychol, Glasgow, Lanark, Scotland
[3] Univ Edinburgh, Neuroimaging Sci, Ctr Clin Brain Sci, Edinburgh, Midlothian, Scotland
来源：
JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION | 2018年 / 88卷 / 16期
关键词：
Tests of independence; multivariate outliers; projection methods; Pearson's correlation; Spearman's rho; HIGH BREAKDOWN; ROBUST;
D O I：
10.1080/00949655.2018.1501051
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
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.
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页码：3116 / 3131
页数：16
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