  # 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!

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

>
> 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')
> );
>
>
>
>
> *
> *   For searches and help try:
> *   http://www.stata.com/support/faqs/res/findit.html
> *   http://www.stata.com/support/statalist/faq
> *   http://www.ats.ucla.edu/stat/stata/
>

*
*   For searches and help try:
*   http://www.stata.com/support/faqs/res/findit.html
*   http://www.stata.com/support/statalist/faq
*   http://www.ats.ucla.edu/stat/stata/
```