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RE: st: Multiple nonlinear equations regression with categorical variables


From   John Kim <tiderunner00@hotmail.com>
To   <statalist@hsphsun2.harvard.edu>
Subject   RE: st: Multiple nonlinear equations regression with categorical variables
Date   Thu, 6 Jan 2011 12:39:23 -0500

Hi Kit and the list,

Thank you for your response. I was trying to avoid transforming the data since that would change the assumptions about variance. Or does it not matter for the predictor variables?

> <>
> I have one dependent variable (continuous) that I would like to explain
> with five independent variables. Four of them are continuous and one is
> categorical. I am looking for a model that would allow me to fit
> different
> nonlinear (exponential, logarithmic) as well as linear equations to
> each of the continuous independent variables. I am also interested in
> testing some of
> the interaction terms in the same model, most notably between the
> categorical and the continuous independent variables. Is there a Stata
> command that
> would allow me to do this? Ideally, the model would also provide some
> indication of which main and interaction terms should be included for
> greatest parsimony.
>
> You can readily fit such models with Stata's regress command. You need merely transform the independent variables as you wish and then estimate the linear regression. These are not 'nonlinear equations', that is, not nonlinear in the parameters, so standard regression will suffice.
>
> Stata 11's support for factor variables (categorical variables) and interactions between them and continuous variables makes it much easier to estimate such interaction models, and test for the significance of interactions, than in earlier versions of Stata.
>
> Kit
>
>
>
> Kit Baum | Boston College Economics & DIW Berlin | http://ideas.repec.org/e/pba1.html
> An Introduction to Stata Programming | http://www.stata-press.com/books/isp.html
> An Introduction to Modern Econometrics Using Stata | http://www.stata-press.com/books/imeus.html
>
>
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