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Re: st: Estimating marginal effects of linear and quadratic term from a logit regression


From   pradeep.kurukulasuriya@yale.edu
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Estimating marginal effects of linear and quadratic term from a logit regression
Date   Mon, 8 Nov 2004 08:54:50 -0500

You are a star! thank you so much for the explanation and time taken 
to answer my question. I will try as you suggest.

Thanks again!
Pradeep


Quoting maartenbuis <maartenbuis@yahoo.co.uk>:

> Dear Pradeep,
> 
> The example I have given can also serve as warning about summerizing
> 
> a nonlinear effect with one parameter. Look at the graph: early on 
> mpg has a very strong effect but it has flattened out when it has 
> reached its mean, so the marginal effect at its mean is very small.
> 
> If you do not plot the probability against the x of interest you 
> might miss these aspects.
> 
> Maarten
> 
> #delim ;
> sysuse auto;
> 
> gen mpg2=mpg^2;
> 
> logit foreign price weight mpg mpg2;
> 
> sum price, meanonly;
> local price = r(mean);
> 
> sum weight, meanonly;
> local weight = r(mean);
> 
> sum mpg, meanonly;
> local mpg = r(mean);
> 
> gen gr_mpg = 11 + _n;
> gen pr=. ;
> 
> forvalues i= 12/41 { ;
> replace pr= invlogit(_b[_cons] + _b[weight]*`weight' + 
> _b[price]*`price' + _b[mpg]*`i' + _b[mpg2]*`i'^2) if gr_mpg==`i' ;
> };
> 
> line pr gr_mpg if gr_mpg <=41, xline(`mpg');
> 
> 
> nlcom(
> exp(_b[_cons] + _b[price]*`price' + _b[weight]*`weight' + _b
> [mpg]*`mpg' + _b[mpg2]*`mpg'^2)/
> (1+exp(_b[_cons] + _b[price]*`price' + _b[weight]*`weight' + _b
> [mpg]*`mpg' + _b[mpg2]*`mpg'^2))^2*
> (_b[mpg]+2*_b[mpg2]*`mpg')
> );
> 
> 
> 
> 
> *
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> 


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