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From |
"Ploutz-Snyder, Robert (JSC-SK)[USRA]" <robert.ploutz-snyder-1@nasa.gov> |

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

Subject |
RE: st: Omnibus effects following xtmelogit with margins |

Date |
Fri, 24 Sep 2010 14:46:01 -0500 |

Thank you Phil for chiming in. Indeed, my one thread has turned into two --one about whether a 2 or 3 level model is best, and the second on my original question about getting omnibus main effects and interactions following xtmelogit. I originally tried anovalator prior to my post but I was not using the predict(passthru) option that you used here. That option is mentioned briefly in the anovalator help file, with much more thorough coverage at http://www.ats.ucla.edu/stat/stata/faq/anovalator.htm (link referenced in the help file). Thank you very much. This is what I needed for my original question (yes, I caught that missing snip of code telling anovalator to run main effects or 2way) ...still contemplating Michaels ideas... Rob -----Original Message----- From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Philip Ender Sent: Friday, September 24, 2010 2:06 PM To: statalist@hsphsun2.harvard.edu Subject: Re: st: Omnibus effects following xtmelogit with margins "Ploutz-Snyder, Robert (JSC-SK)[USRA]" wrote ... I also ran into a snag using -margins- as I usually do after an -xtmixed- model to obtain omnibus main effects for an ordinal factor variable. ... But my use of -margins- to get the omnibus main effect for time (as I would with xtmixed) failed: . margins time, asbalanced atmeans default prediction is a function of possibly stochastic quantities other than e(b) r(498); ---------------------- Robert- I've been following your discussion with Michael Mitchell about the design of your analysis. I would like to pick up on your second question concerning using -margins-, for which I have two comments. 1) The default predictor for -xtmelogit- is mu which has uses both fixed and random effects. If you are interested in having the predictive margins scaled as a linear predictor, you can use . margins time, asbalanced atmeans predict(xb) If you want to have your predictive margins scaled as a probabilities, then -margins- can (will) only use the fixed effects of the model, like this. . margins time, asbalanced atmeans predict(mu fixedonly) 2) In any case, neither of the above is a "true" main effect because the factor variables use dummy coding. You can use the -anovalator- to get main effects (findit anovalator). . anovalator time, predict(xb) /* or */ . anovalator time, predict(mu fixedonly) I hope this is not too confusing. Phil -- Phil Ender UCLA Statistical Consulting Group * * 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/ * * 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**:**Re: st: Omnibus effects following xtmelogit with margins***From:*Philip Ender <ender97@gmail.com>

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