Notice: On March 31, it was **announced** that Statalist is moving from an email list to a **forum**. The old list will shut down at the end of May, and its replacement, **statalist.org** is already up and running.

[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]

From |
"Nick Cox" <n.j.cox@durham.ac.uk> |

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

Subject |
st: RE: Using mixlogit as a substitute of xtlogit. |

Date |
Fri, 4 Jun 2010 10:19:05 +0100 |

The missing reference here is . search mixlogit Keyword search Keywords: mixlogit Search: (1) Official help files, FAQs, Examples, SJs, and STBs Search of official help files, FAQs, Examples, SJs, and STBs SJ-7-4 st0133_1 . . . . . . . . . . . . . . . . Software update for mixlogit (help mixlogit if installed) . . . . . . . . . . . . . . . A. R. Hole Q4/07 SJ 7(4):593 estimation speed improved and new options added for specifying weights and for obtaining robust and cluster- robust standard errors SJ-7-3 st0133 . . Fitting mixed logit models using max. simulated likelihood (help mixlogit if installed) . . . . . . . . . . . . . . . A. R. Hole Q3/07 SJ 7(3):388--401 fits mixed logit models by using maximum simulated likelihood To spell out the logic, which is important: 1. Arne Risa Hole did a good job with -mixlogit- and deserves a nod of recognition. (I'll tuck in here a comment that the Stata Journal is always happy to get publicity like this.) 2. Someone, especially anyone new or inexperienced in Stata use, might be intrigued by a posting like this and type -help mixlogit- and then be mystified by the error message. Giving a one-sentence explanation that this is a user-written command that you must install from the SJ site would save such people from wasting their time trying to work out what they did wrong. Nick n.j.cox@durham.ac.uk ippab ippab I am wondering if there is any benefit of using mixlogit for a binary dependent variable in a panel data. Basically, to use mixlogit, I will have to create two alternatives (which are complementary), an alternative specific constant, and interactions between independent variables and the alternative specific constant. Is this is a wise thing to do? My vague understanding is that mixlogit allows for more heterogeneity than xtlogit. The other thing I noticed is that, for normally distributed parameters, we can find out what percentage of the population is on the other side of zero. But, I am confused about interpreting a population average beta obtained from xtlogit in light of estimates from mixlogit. Just to give an example, if the estimate for x1 is 2.05 from xtlogit, the interpretation would be that increasing x1 increases the the likelihood of y=1. Now, getting a similar estimate from mixlogit, e.g., mean is 2.5 for x1 with std 3.10, makes the interpretation complicated. This means for about 20.9% of the sample, increasing x1 does not increase the likelihood of y=1. Am I understanding these correctly? The more critical question is, if more than 20% or 30% of the sample have different preference, what does it mean to have a positive significant coefficient (mean)? * * 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: Using mixlogit as a substitute of xtlogit.***From:*ippab ippab <ippab.statalist@gmail.com>

- Prev by Date:
**st: RE: saving graphs for publication** - Next by Date:
**Re: st: RE: RE: RE: Stata updated to 11.1** - Previous by thread:
**Re: st: Using mixlogit as a substitute of xtlogit.** - Next by thread:
**st: SSC Archive** - Index(es):