When coming to Kendall's tau-b it's easy to find values interpretations but difficult to find references to support them. Can anybody help me with that? Thanks a million.
Kendall’s rank correlation coefficient is a nonparametric measure of association between two ordinal variables. It could be recommended over Spearman’s coefficient, which is also a nonparametric test, if the data set is small, with many tied ranks. The following publications could be of interest.
Brossart, D. F., Laird, V. C., & Armstrong, T. W. (2018). Interpreting Kendall’s Tau and Tau-U for single-case experimental designs. Cogent Psychology, 5(1), 1518687. https://doi.org/10.1080/23311908.2018.1518687
Kamnitui, N., Genest, C., Jaworski, P., & Trutschnig, W. (2019). On the size of the class of bivariate extreme-value copulas with a fixed value of Spearman’s rho or Kendall’s tau. Journal of Mathematical Analysis and Applications, 472(1), 920–936. https://doi.org/10.1016/j.jmaa.2018.11.057
Nowak, C. P., & Konietschke, F. (2021). Simultaneous inference for Kendall’s tau. Journal of Multivariate Analysis, 185, 104767. https://doi.org/10.1016/j.jmva.2021.104767
Shih, J. H., & Fay, M. P. (2017). Pearson’s chi-square test and rank correlation inferences for clustered data. Biometrics, 73(3), 822–834. https://doi.org/10.1111/biom.12653
Good luck,
Cordinant and discordinant are the keys which differentiates the two. Kendall differentiates strongly and more accurately between two observations. It gives the probability of the two observations while correlation only shows the strength between the two.
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