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From |
Arne Risa Hole <arnehole@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: MIXLOGIT: marginal effects |

Date |
Mon, 6 Feb 2012 14:03:39 +0000 |

Thanks Maarten. Just a small clarification: -mixlogit- allows for multinomial outcomes while -xtmelogit- is for binary outcomes only so the two are not substitutes in general. Another difference is that -mixlogit- uses simulation to approximate the likelihood function, while -xtmelogit- uses quadrature. For more information about -mixlogit- see <http://www.stata-journal.com/article.html?article=st0133>. I disagree when it comes to marginal effects: I personally find them much easier to interpret than odds-ratios. In the end the choice will depend on your discipline and personal preference. Arne On 6 February 2012 13:29, Maarten Buis <maartenlbuis@gmail.com> wrote: > On Mon, Feb 6, 2012 at 1:57 PM, Davide Castellani wrote: >> I am new to the mixlogit program. I was wondering how to work out marginal >> effects ( and SEs of MEs). > > -mixlogit- is a user writen program, so per the Statalist FAQ (url at > the bottom of every post on Statalist) you must say where you got it > from. I will assume that you got it from the SSC archive, i.e. you > used -ssc install mixlogit- to install -mixlogit-. > > It seems that -mixlogit- does not contain a standard predict function, > so that means you cannot use any of the standard methods like > -margins- or -mfx-. > > Since you did not say which version of Stata you are using, we will > have to asume (again per the Statalist FAQ) that it is Stata 12. In > that case you can just use the official -xtmelogit- command. This will > allow you to use -margins- to get marginal effects at the average > values (or other typical values) of the explanatory variables. > However, many people seem to want average marginal effects, which is > not the same. This is much harder to obtain. > > In general, I would just interpret the odds ratios. I do not > understand why people go through a lot of trouble fitting a non-linear > model and than undoing all that effort by only reporting marginal > effects, which in effect reduces your non-linear model to a linear > model. If you wanted a linear model, than why not fit a linear model? > If you think a linear model is unacceptable in your case or in > general, than so are marginal effects. > > Hope this helps, > Maarten > > -------------------------- > Maarten L. Buis > Institut fuer Soziologie > Universitaet Tuebingen > Wilhelmstrasse 36 > 72074 Tuebingen > Germany > > > http://www.maartenbuis.nl > -------------------------- > * > * 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/

**Follow-Ups**:**Re: st: MIXLOGIT: marginal effects***From:*Maarten Buis <maartenlbuis@gmail.com>

**R: st: MIXLOGIT: marginal effects***From:*"Davide Castellani" <davide.castellani@unibg.it>

**References**:**Re: st: MIXLOGIT: marginal effects***From:*Maarten Buis <maartenlbuis@gmail.com>

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