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Re: st: too large standard errors of marginal effects aftermultinomial logit model


From   [email protected]
To   [email protected]
Subject   Re: st: too large standard errors of marginal effects aftermultinomial logit model
Date   Wed, 31 May 2006 15:11:08 -0400 (EDT)

Hi Richard,

Thank you very much. I checked the std. dev. of explanatory variables within 
each category of y, and found that three missing dummy variables had no 
variability, which actually caused the problem. Once I excluded these 
variables, the standard errors of marginal effects became reasonable. The -
margeff- command works well and really fast. Thanks a lot.

Duan

Duan Peng
Department of Economics
University of Miami

Quoting Richard Williams <[email protected]>:

> At 03:23 PM 5/30/2006, [email protected] wrote:
> >When I calculate the marginal effects after multinomial logit model
> using the
> >command "mfx compute, predict (outcome(1))", Stata gives me very 
> >large standard
> >errors and all p values are equal to 1. Dose anyone know the reason of
> this
> >problem and how to solve it? Many thanks.
> 
> You might try getting the -margeff- command from SSC and see if it 
> fares any better.  If nothing else, it is faster.  Include the 
> -at(mean)- option to make it comparable to mfx.
> 
> You might also try something like
> 
> bysort y: sum x1 x2 x3 x4
> 
> This will show you if, say, one or more of the xs has little or no 
> variability within a category of y.  That can sometimes cause 
> problems.  With multiple-outcome models like mlogit or gologit2, 
> spreading the data too thin can create complications.
> 
> 
> -------------------------------------------
> Richard Williams, Notre Dame Dept of Sociology
> OFFICE: (574)631-6668, (574)631-6463
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> HOME:   (574)289-5227
> EMAIL:  [email protected]
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> WWW (department):    http://www.nd.edu/~soc 
> 
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