Rodgers, J.L. and Nicewander, W.A. (1988) Thirteen Ways to Look at the Correlation Coefficient. The American Statistician, 42, 59-66.
https://doi.org/10.2307/2685263

has been cited by the following article:

• TITLE: A Note on the Relationship between the Pearson Product-Moment and the Spearman Rank-Based Coefficients of Correlation

  AUTHORS: Todd Christopher Headrick

  KEYWORDS: Bivariate Normal Distribution, Product-Moment Correlation, Rank-Based Correlation, Gibbs Phenomenon

  JOURNAL NAME: Open Journal of Statistics, Vol.6 No.6, November 17, 2016

  ABSTRACT: This note derives the relationship between the Pearson product-moment coefficient of correlation and the Spearman rank-based coefficient of correlation for the bivariate normal distribution. This new derivation shows the relationship between the two correlation coefficients through an infinite cosine series. A computationally efficient algorithm is also provided to estimate the relationship between the Pearson product-moment coefficient of correlation and the Spearman rank-based coefficient of correlation. The algorithm can be implemented with relative ease using current modern mathematical or statistical software programming languages e.g. R, SAS, Mathematica, Fortran, et al. The algorithm is also available from the author of this article.