Dear Saurav,
If you don't wish to calculate it by hand, you can extract the Inverse Mill's
Ratio using the function "invMillsRatio" from the sampleSelection package.
(http://cran.r-project.org/web/packages/sampleSelection/index.html).
You can also use the "heckit" function in the same package for estimating the
entire model.
And are you sure you wish to drop the non-significant selection variable? If
your theoretical model is sound you might end up with an omitted variable bias
...
Good luck,
Uli
> Date: Sat, 11 Jul 2009 13:39:43 +0100
> From: saurav pathak <pathak.sau...@gmail.com>
> Subject: [R] Heckman Selection Model/Inverse Mills Ratio
> To: r-help@r-project.org
>
> I have so far used the following command
>
> glm(formula = s ~ age + gender + gemedu + gemhinc +
> es_gdppc +
> imf_pop + estbbo_m, family = binomial(link =
> "probit"))
>
> My question is
> 1. How do i discard the non significant selection variables
> (one out of the
> seven variables above is non-significant) and calculate the
> Inverse Mills
> Ratio of the significant variables
>
> 2. I need the inverse mills ratio from the above to run the
> outcome equation
> model using OLS with the Inverse mills ratio as the control
> for selection
> bias, kindly help, hence I need to get the IMR
>
> 3. How can this eb done in R using my concept or otherwise
> does there exist
> anotehr way of doing what I wish to achieve
> Please help
> Thanks#
> Saurav
>
> --
> Dr.Saurav Pathak
> PhD, Univ.of.Florida
> Mechanical Engineering
> Doctoral Student
> Innovation and Entrepreneurship
> Imperial College Business School
> s.patha...@imperial.ac.uk
> 0044-7795321121
>
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