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From |
Stas Kolenikov <skolenik@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Correlation of Dummy and Metric Variables? |

Date |
Mon, 21 Sep 2009 14:20:37 -0500 |

In psychometrics, there are concepts of polychoric and polyserial correlations. The first one is between two ordinal variables, and the second one is between an ordinal variable and a continuous variable. If your variables are truly nominal (like gender or geography), then the correlations are likely meaningless, although you can meaningfully ask whether the distributions of the continuous variables differ between the values of the discrete variable (answered by ANOVA, Kruskal-Wallis test and such). I wrote -polychoric- package some while ago that computes these correlations. On Mon, Sep 21, 2009 at 9:45 AM, Christian Weiß <mail@cweiss.org> wrote: > Dear Statalist, > > although it's not a particularly Stata specific question , I am hoping > to get advise on the following (basic?) question: > > > I am using the following command to get a correlation matrix > > quietly estpost correlate `vars', matrix > esttab using correlations.csv, not unstack compress noobs star(* 0.10 > ** 0.05 *** 0.01) long b(%9.2f) replace > > `vars' containts a battery of mostly metric variables. Besides the > metric variables, there is also three dummy variables. > > I am wondering now if the reported (relatively high) correlation > coefficients among the dummy variables and between some of the metric > variables and the dummy variables are actually meaningful. How to > interpret them / which correlation test to use? > -- Stas Kolenikov, also found at http://stas.kolenikov.name Small print: I use this email account for mailing lists only. * * 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/

**References**:**st: Correlation of Dummy and Metric Variables?***From:*Christian Weiß <mail@cweiss.org>

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