[R] interaction effects in probits
Tobias Muhlhofer
tmuhlhof at indiana.edu
Thu Apr 17 21:46:04 CEST 2008
Dear R-listers,
I am trying to compute interaction effects in a probit model, and
conduct hypothesis tests on these effects correctly.
Specifically, I have a model of the form y = a + b1 m + b2 x + b3 m*x,
where both y and m are 0-1 dummies, x is continuous, and I am
interested in the sign and statistical significance of the marginal
effect for observations for which m=1, over the base (obs for which
m=0). Then, I also want to conduct a test of the hypothesis H0: b2 +
b3 = 0.
As we know, probits are non-linear models, and so coefficients of
interaction variables do not carry the usual interpretation of
marginal effects over the base. Instead, I think what one needs to do
is compute the cross-derivative of y with respect to x and m.
Is there an efficient way of doing this in R preferably after having
estimated this model through glm(<formula>, family = binomial(link =
probit))? Can anyone suggest any code?
Thanks!
--
Dr. Tobias Mühlhofer
Assistant Professor
Department of Finance
Kelley School of Business
Indiana University
Tel: +1 812 855 9270
http://tobias.muhlhofer.com
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