Spearman’s Rank Correlation Tests (Simulation)

On the Permutation Distribution of Independence Tests

One of the most popular class of tests for independence between two random variables is the general class of rank statistics which are invariant under permutations. This class contains Spearman’s coefficient of rank correlation statistic, Fisher-Yates statistic, weighted Mann statistic and others. Under the null hypothesis of independence these test statistics have a permutation distribution th...

Constructing Confidence Intervals for Spearman’s Rank Correlation with Ordinal Data: A Simulation Study Comparing Analytic and Bootstrap Methods

Forward Selection Procedure for Linear Model Building Using Spearman’s Rank Correlation

Forward selection (FS) is a step-by-step model-building algorithm for linear regression. The FS algorithm was expressed in terms of sample correlations where Pearson’s product-moment correlation was used. The FS yields poor results when the data contain contaminations. In this article, we propose the use of Spearman’s rank correlation in FS. The proposed method is called FSr. We conduct an exte...

Multivariate Spearman’s rho for rank aggregation

We study the problem of rank aggregation: given a set of ranked lists, we want to form a consensus ranking. Our main contribution is the derivation of a nonparametric estimator for rank aggregation based on multivariate extensions of Spearman’s ρ, which measures correlation between a set of ranked lists. Multivariate Spearman’s ρ is defined using copulas, and we show that the geometric mean of ...

Multivariate Spearman’s ρ for Aggregating Ranks Using Copulas

We study the problem of rank aggregation: given a set of ranked lists, we want to form a consensus ranking. Furthermore, we consider the case of extreme lists: i.e., only the rank of the best or worst elements are known. We impute missing ranks and generalise Spearman’s ρ to extreme ranks. Our main contribution is the derivation of a non-parametric estimator for rank aggregation based on multiv...