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

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: conditional SE of y|X in glm |

Date |
Tue, 24 Apr 2012 09:57:25 +0100 |

See -glmcorr- (SSC) for one approach here. That calculates an rmse which appears similar, if not identical, to what you want. I like to have such measures accessible for comparing -glm- results with those of other models in which rmse appears naturally. Perhaps it is a comfort blanket, but there you go. Note that putting a constant into a variable is usually overkill as di sqrt(e(dispers)) does the calculation. Use a scalar or local macro if you want to store the value. On Tue, Apr 24, 2012 at 9:31 AM, Marco Ventura <mventura@istat.it> wrote: > from a GLM estimate I want to retrieve the conditional standard error of y > given the covariates. If I do > > gen sigma=sqrt(e(dispers)) > > do I always get the right thing independently of any family and link? > Should I correct it by sqrt(e(dispers)* (_N-1)/_N)? > And do you think I should instead use the Pearson residuals such as > > gen sigma=sqrt(e(dispers_p)) > * * 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: conditional SE of y|X in glm***From:*Marco Ventura <mventura@istat.it>

**References**:**st: conditional SE of y|X in glm***From:*Marco Ventura <mventura@istat.it>

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