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Confidence intervals for Kendall's tau
Author(s) -
Long Jeffrey D.,
Cliff Norman
Publication year - 1997
Publication title -
british journal of mathematical and statistical psychology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.157
H-Index - 51
eISSN - 2044-8317
pISSN - 0007-1102
DOI - 10.1111/j.2044-8317.1997.tb01100.x
Subject(s) - statistics , confidence interval , mathematics , normality , variance (accounting) , correlation , population , sample size determination , monotonic function , range (aeronautics) , econometrics , demography , mathematical analysis , materials science , geometry , accounting , sociology , business , composite material
A simulation study was conducted to examine the performance of several confidence intervals (CIs) for Kendall's tau ( t xy ) under a variety of population conditions. Two normal population variables ( N = 10,000) were transformed to have tau correlations, τ = 0, .19, .41, or.71. Samples ( n = 10, 50, 200) were drawn from the transformed populations 2000 times under each level of correlation, and accompanying CIs were computed on each sample. The results show that the CI for τ based on a consistent estimate of the variance of t xy has the best coverage and power among a number of alternatives. Kendall's t xy is unaffected by non‐normality induced by monotonic transformations and, with its consistent variance estimated from the sample, performs well under a wide range of conditions.

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