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

 From "maartenbuis" To statalist@hsphsun2.harvard.edu Subject Re: st: Estimating marginal effects of linear and quadratic term from a logit regression Date Mon, 08 Nov 2004 11:28:20 -0000

```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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```