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From |
Felix Wilke <felixw83@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Plot probability function after xtlogit, re - how to interpret constant? |

Date |
Thu, 23 May 2013 15:27:28 +0200 |

Dear Maarten, thanks for your suggestion to use margins. I will certainly have a look at my predictions with marginsplot as well. But as you already stated, that does not really solve my problem. The following example shows what I mean: *** webuse union xtlogit not_smsa age, re twoway function befristet= exp(_b[_cons]+_b[age]*x)/(1+exp(_b[_cons]+_b[age]*x)) logit not_smsa age twoway function y= exp(_b[_cons]+_b[age]*x)/(1+exp(_b[_cons]+_b[age]*x)) ** the relative frequency of not_smsa is about 0.28 the logit estimation suggests probabilities around 0.2 depending on age. the xtlogit, re estimation however suggests probabilities around 0.005 depending on age. *centering age does not change these results substantially* So my question remains how to interpret these probabilities. Felix On 23 May 2013 13:52, Maarten Buis <maartenlbuis@gmail.com> wrote: > On Thu, May 23, 2013 at 1:19 PM, Felix Wilke wrote: >> I have some longitudinal models (xtlogit, re) containing interaction effects. >> Now I would like to plot the effect of the interaction effects. >> Therefore I use a function like the following (x2 being a dummy >> variable): >> >> twoway function >> y0=exp(_b[_cons]+_b[x1]*x)/(1+exp(_b[_cons]+_b[x1]*x)), range(0 4) || >> function y1=exp(_b[_cons]+_b[x2]+_b[x1]*x+_b[interaction_x1x2]*x)/(1+exp(_b[_cons]+_b[x2]+_b[x1]*x+_b[interaction_x1x2]*x)) > > This strategy may work, but it is just too easy to create a typo or > bug this way. It is much safer to use -margins- and the -marginsplot- > command. > > *------------------ begin example ------------------ > webuse union > xtlogit union age grade i.not_smsa south##c.year > margins, at(age=30 grade=12 not_smsa=1 /// > south=(0 1) year=(70/88)) /// > predict(pu0) > marginsplot, x(year) > *------------------- end example ------------------- > (For more on examples I sent to the Statalist see: > http://www.maartenbuis.nl/example_faq ) > >> The shape of the function display the effects as expected. My problem, >> however, is the estimated probability. It is unrealistic low - if I >> repeat the same regression as a cross-section analysis I get proper >> probabilities. >> >> I guess the constant in an xtlogit,re model is to be interpreted >> differently than in a cross sectional logit model. Is this right? > > Not really, it is still the expected log odds of success when all > covariates equal 0. This now includes the group level error term, but > the value 0 there refers to an average group, so that is not the > source of your problem. > >> And how do I interpret the estimated probabilities in a xtlogit, re model? > > Just as you would any other probability. > > Hope this helps, > Maarten > > --------------------------------- > Maarten L. Buis > WZB > Reichpietschufer 50 > 10785 Berlin > Germany > > http://www.maartenbuis.nl > --------------------------------- > * > * 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/ * * 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: Plot probability function after xtlogit, re - how to interpret constant?***From:*Felix Wilke <felixw83@gmail.com>

**Re: st: Plot probability function after xtlogit, re - how to interpret constant?***From:*Maarten Buis <maartenlbuis@gmail.com>

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