Calculation and statistic test of partial correlation of general correlation measures
Wenjun Zhang
Abstract
Wenjun Zhang
Abstract
It is well known that Pearson linear correlations between more than two attributes (nodes, taxa, variables, etc) can be adjusted to partial linear correlations for eliminating indirect between-attribute interactions of other attributes not being tested. In present study I first proposed three correlation measures, revised Dice coefficient, overlap coefficient, and proportion correlation. In addition, I proposed partial correlation measures for some correlation measures, of which Jaccard correlation, revised Dice coefficient, overlap coefficient, and point correlation are for binary attributes; Spearman rank correlation and proportion correlation are for interval value attributes. The full algorithm and Matlab codes (Pearson linear correlation is included also) are given. Users can add other general correlation measures in the Matlab codes. \n
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It is well known that Pearson linear correlations between more than two attributes (nodes, taxa, variables, etc) can be adjusted to partial linear correlations for eliminating indirect between-attribute interactions of other attributes not being tested. In present study I first proposed three correlation measures, revised Dice coefficient, overlap coefficient, and proportion correlation. In addition, I proposed partial correlation measures for some correlation measures, of which Jaccard correlation, revised Dice coefficient, overlap coefficient, and point correlation are for binary attributes; Spearman rank correlation and proportion correlation are for interval value attributes. The full algorithm and Matlab codes (Pearson linear correlation is included also) are given. Users can add other general correlation measures in the Matlab codes. \n
Key concepts: Correlation, Correlation coefficient, Spearman's rank correlation coefficient, Fisher transformation, Statistics, Correlation ratio, Partial correlation, Mathematics