is about
effect size estimate
correlation coefficient
Spearman's rank correlation coefficient
2
Orlaith Burke
Alejandra Gonzalez-Beltran
Philippe Rocca-Serra
Spearman's rank correlation coefficient is a correlation coefficient which is a nonparametric measure of statistical dependence between two ranked variables. It assesses how well the relationship between two variables can be described using a monotonic function. If there are no repeated data values, a perfect Spearman correlation of +1 or −1 occurs when each of the variables is a perfect monotone function of the other.
Spearman's coefficient may be used when the conditions for computing Pearson's correlation are not met (e.g linearity, normality of the 2 continuous variables) but may require a ranking transformation of the variables
Spearman's rho
cor(x, y = NULL, use = "everything",method = c("spearman"))
http://en.wikipedia.org/wiki/Spearman%27s_rank_correlation_coefficient
scipy.stats.spearmanr(a, b=None, axis=0)
http://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.spearmanr.html#scipy.stats.spearmanr
source:
https://github.com/scipy/scipy/blob/v0.15.1/scipy/stats/stats.py#L2643
ordinal variable
ready for release