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From |
Chiara Mussida <cmussida@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: predict after mlogit estimation |

Date |
Fri, 16 Mar 2012 16:46:24 +0100 |

Thanks Richard, the 1st method seems more "precise". I will go for that one. Nonetheless, the differnece between the two cases is not that much relevant, on average. More precisely, some p's are almost equas, other not with a discrepancies of (ar max) 0,018. On 16/03/2012, Richard Williams <richardwilliams.ndu@gmail.com> wrote: > At 04:09 AM 3/16/2012, Chiara Mussida wrote: >>Thank you Richard, >>this seems to be the solution. Anyway, is it possible to check whether >>the results obtained for p1 p2 p3 are the ones I need (male >>coefficients*female individual characteristics)? >>Male coefs are in the stata output, whilst female characteristics in >>my dataset. Should I compute the product between the coefs in the >>output and the average individual characteristics of female? >> >>Thanks to you all >>chiara > > If you want a 2nd opinion, try > > use "http://www.indiana.edu/~jslsoc/stata/spex_data/ordwarm2.dta";, clear > mlogit warm yr89 white age ed prst if male == 1 > predict p1 p2 p3 p4 if male==0 > sum p1 p2 p3 p4 > margins if male == 0, noesample predict(outcome(1)) > margins if male == 0, noesample predict(outcome(2)) > margins if male == 0, noesample predict(outcome(3)) > margins if male == 0, noesample predict(outcome(4)) > > Note that this is NOT the same as plugging in the average individual > characteristics of females. If you wanted to do that, the commands would be > > margins if male == 0, noesample predict(outcome(1)) atmeans > margins if male == 0, noesample predict(outcome(2)) atmeans > margins if male == 0, noesample predict(outcome(3)) atmeans > margins if male == 0, noesample predict(outcome(4)) atmeans > * verify that female means were used by margins > sum yr89 white age ed prst if male==0 > > With the first approach, you are computing a prediction for each case > and then averaging the predictions. With the 2nd approach, you are > computing the predicted value for a person who had average values on > all the independent variables. I generally prefer the first approach. > It often doesn't make that much difference in practice, but sometimes it > will. > > If you want yet a 3rd opinion, I suppose you could do the > calculations for a few cases, or write your own gen command instead > of using predict. > > > ------------------------------------------- > Richard Williams, Notre Dame Dept of Sociology > OFFICE: (574)631-6668, (574)631-6463 > HOME: (574)289-5227 > EMAIL: Richard.A.Williams.5@ND.Edu > WWW: http://www.nd.edu/~rwilliam > > * > * 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/ > -- Chiara Mussida PhD candidate Doctoral school of Economic Policy Catholic University, Piacenza (Italy) * * 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: predict after mlogit estimation***From:*Chiara Mussida <cmussida@gmail.com>

**Re: st: predict after mlogit estimation***From:*Richard Williams <richardwilliams.ndu@gmail.com>

**Re: st: predict after mlogit estimation***From:*Chiara Mussida <cmussida@gmail.com>

**Re: st: predict after mlogit estimation***From:*Richard Williams <richardwilliams.ndu@gmail.com>

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