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A WEIGHTED RANK MEASURE OF CORRELATION
Author(s) -
Pinto da Costa Joaquim,
Soares Carlos
Publication year - 2005
Publication title -
australian and new zealand journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.434
H-Index - 41
eISSN - 1467-842X
pISSN - 1369-1473
DOI - 10.1111/j.1467-842x.2005.00413.x
Subject(s) - mathematics , spearman's rank correlation coefficient , rank correlation , measure (data warehouse) , rank (graph theory) , statistics , correlation coefficient , correlation , correlation ratio , fisher transformation , distance correlation , table (database) , pearson product moment correlation coefficient , combinatorics , data mining , random variable , computer science , geometry
Summary Spearman's rank correlation coefficient is not entirely suitable for measuring the correlation between two rankings in some applications because it treats all ranks equally. In 2000, Blest proposed an alternative measure of correlation that gives more importance to higher ranks but has some drawbacks. This paper proposes a weighted rank measure of correlation that weights the distance between two ranks using a linear function of those ranks, giving more importance to higher ranks than lower ones. It analyses its distribution and provides a table of critical values to test whether a given value of the coefficient is significantly different from zero. The paper also summarizes a number of applications for which the new measure is more suitable than Spearman's.