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From |
"Nick Cox" <n.j.cox@durham.ac.uk> |

To |
<statalist@hsphsun2.harvard.edu> |

Subject |
RE: st: difference between "Spearman" and "pwcorr / correlate" |

Date |
Thu, 8 Oct 2009 17:33:17 +0100 |

There's a tacit criterion here, that techniques must have simple verbal interpretations. I am as much in favour of simple verbal interpretations as the next person -- nay, on average, more so -- but while they're a bonus when available insisting on them would deprive you of much that is indispensable. What's the simple verbal interpretation of (say) eigenvectors or an SVD? Nick n.j.cox@durham.ac.uk Stas Kolenikov If you have a finite population, then of course you will have Spearman correlation for it. Although if you want to set up any asymptotic framework, you will be trying to hit a moving target. I don't think there is a meaningful definition of Spearman correlation for infinite populations/continuous variables, although I might be mistaken. On the other hand, Kendall's tau, as Nick Cox quoted from Roger Newson, has explicit population analogues in probabilities of concordant and discordant pairs of observations. The question is: if the correlation estimate is 0.5, what does it say? For Pearson moment correlation, it means that the proportion of explained variance in a bivariate regression is 0.25. For Kendall's tau, it means that for every discordant pair of observations, there are three concordant pairs (i.e., Prob[ concordant ] = 3 Prob[ discordant ] = 3/4 ). For Spearman rank correlation, you can only say that the variables are positively associated, but not much more. * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**Re: st: difference between "Spearman" and "pwcorr / correlate"***From:*Stas Kolenikov <skolenik@gmail.com>

**References**:**Re:st: difference between "Spearman" and "pwcorr / correlate"***From:*Mike Lacy <Michael.Lacy@colostate.edu>

**Re: st: difference between "Spearman" and "pwcorr / correlate"***From:*Stas Kolenikov <skolenik@gmail.com>

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