Also, as Frank Harrell writes (in the context of model building): "When
Y is binary or continuous (but not censored), a good general-purpose
measure of association that is useful in making decisions about the
number of parameters to devote to a predictor is an extension of
Spearman's rho rank correlation. This is the ordinary R^2 from
predicting the rank of Y based on the rank of X and the square of the
rank of X. This rho^2 will not only detect nonlinear relationships (as
will the ordinary Spearman rho) but nonmonotonic ones as well."

SR Millis

"Wuensch, Karl L" wrote:
> 
> Rich said "Spearman's, especially, serve no end that I think of."
> 
> I'm probably taking this out of the context of the thread, but Spearman
rho
> is a potentially useful statistic if you wish to measure the
monotonicity of
> a relationship rather than the linearity.

~~~~~~~~~~~~~~~~~~~~~~~~~~
Scott R. Millis, PhD, ABPP (CN, RP)
KMRREC Research
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