Computing interaction effects and standard errors in logit and probit models
Edward C. Norton
Department of Health Policy and Administration
University of North Carolina at Chapel Hill
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Hua Wang
Department of Health Policy and Administration
University of North Carolina at Chapel Hill
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Chunrong Ai
Department of Economics
University of Florida and Tsinghua University, China
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Abstract. This paper explains why computing the marginal effect of a change in two
variables is more complicated in nonlinear models than in linear models.
The command inteff computes the correct marginal effect of a change
in two interacted variables for a logit or probit model, as well as the
correct standard errors. The inteff command graphs the interaction
effect and saves the results to allow further investigation.
View all articles by these authors:
Edward C. Norton, Hua Wang, Chunrong Ai
View all articles with these keywords:
inteff, interaction terms, logit, probit, nonlinear models
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