thanks Ajit kumar Roy

A near example is the list of scientific journals in the rankings JCR and SJR. For ranking them both lists use the number of cites of each journal in the last years. These number of cites are the data for ranking the journals each year.

https://www.scimagojr.com/

Dear Colleague Groen,

First of all, I have a question for you; - Why you chose Kendall Tau-b data analysis?

Namely, according to Hill & Lewicky (2007), cit: "Kendall Tau is equivalent to the Spearman R statistic with regard to the underlying assumptions. It is also comparable in terms of its statistical power. However, Spearman R and Kendall tau are usually not identical in magnitude because their underlying logic, as well as their computational formulas are very different. Siegel and Castellan (1988) express the relationship of the two measures in terms of the inequality. More importantly, Kendall tau and Spearman R imply different interpretations: While Spearman R can be thought of as the regular Pearson product-moment correlation coefficient as computed from ranks, Kendall tau rather represents a probability" (please see: StatSoft, Inc. (2013). Electronic Statistics Textbook. Tulsa, OK: StatSoft. WEB: http://www.statsoft.com/textbook/). On other words, I always prefer Spearman's Rank Order Correlations when I have a typical situation in which I have to use some non-parametric statistical anaylsis to detect the correlation and the strength of correlation according to Roemer-Orphale scale. So, I strongly suggest you to use Spearman's rank order correlations and the values of its rs are corresponding to Roemer-Orphae scale. Moreover, the almost every statistical software is calculating automatically significance of rs values and somehow the significant rs values with p lwss than 0.05 are marked. So, use the Spearman's rank order correlations. That's all I can tell you, because I have not direct insight in your work and data. But, if your sample is very small you can definitely use Kendall's Tau, because Kendall’s Tau: usually smaller values than Spearman’s rho correlation. Calculations based on concordant and discordant pairs. Insensitive to error. p values are more accurate with smaller sample sizes. On the other hand, Spearman’s rank order correlation coeffitioent usually have larger values than Kendall’s Tau and it is much more sensitive to error and discrepancies in data. So, without insight to your work and data I can't give you a good advice.

Yours Sincerely, Siniša Srečec

Thanks a lot! Siniša Srečec