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From |
"JVerkuilen (Gmail)" <jvverkuilen@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: mlogit problem |

Date |
Sun, 17 Feb 2013 23:29:57 -0500 |

On Sun, Feb 17, 2013 at 7:31 PM, saqlain raza <bhatti_sb@yahoo.com> wrote: > Thanks JVerkuilen for your response. N=360. For regression models it's good practice to maintain a minimum of 10-20 observations per parameter, which is ordinarily the number of variables. With mlogit, you need to multiply the number of variables by K-1 where K is the number of categories because there is a parameter for each category by variable combination, less the reference category. Even so I'd err on the high side. Thus I'd suggest with your data you can afford something like 6-12 variables to have a chance at having reasonably well-defined coefficients with sensible asymptotic standard errors given your sample size. Even when your model is running, the parameters must be completely wonky. If the standard errors are huge that's a sign. Yes I want to do variables selection for my study. If this is not a good idea, what should I do? > Thanks again for your cooperation Others have addressed this point as well as I think is even possible. You're hoping for a miracle. Jay * * 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: mlogit problem***From:*saqlain raza <bhatti_sb@yahoo.com>

**Re: st: mlogit problem***From:*"JVerkuilen (Gmail)" <jvverkuilen@gmail.com>

**Re: st: mlogit problem***From:*saqlain raza <bhatti_sb@yahoo.com>

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