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From |
Nick Cox <njcoxstata@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: xtmixed for non-parametric outcome |

Date |
Wed, 19 Dec 2012 11:34:30 +0000 |

The nature of your outcome isn't clear beyond an assertion that it is not normally distributed. Even that need not be a problem as the marginal distribution of the response is often of secondary importance. In a simpler situation, suppose x is uniformly distributed and y is generated by a + bx + normal error with mean 0 and some variance. Is it better for the variance to be very small, so that the marginal distribution of y is approximately uniform? Or for it to be very large so that the marginal distribution is closer to normal? In your case, you might consider a transformation of the response. On a related note, I don't think data are best described as non-parametric; there are techniques so described, but in either case the term is not informative. (Arguably, the best such techniques do estimate some parameter such as probability(Y > X).) Nick On Wed, Dec 19, 2012 at 11:12 AM, Nikolaos Pandis <npandis@yahoo.com> wrote: > I am trying to run random effects model for continuous data with 3 categorical predictors (xtmixed). > My outcome is not normally distributed and neither are the residuals after fitting the model. > Question: is anyone aware of any Stata commands for non-parametric correlated data. * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/faqs/resources/statalist-faq/ * http://www.ats.ucla.edu/stat/stata/

**References**:**st: xtmixed for non-parametric outcome***From:*Nikolaos Pandis <npandis@yahoo.com>

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