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Re: st: Scoring a Fixed Effects Model on another dataset


From   Lucas <lucaselastic@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Scoring a Fixed Effects Model on another dataset
Date   Wed, 12 Jun 2013 12:53:13 -0700

This is an interesting question.  I always thought that fixed effects
models give you very good causal effect estimates, but technically the
estimates do not apply beyond the sample.

Think about it like this: the fixed, subject-specific terms (call them
b_0i) capture the effects of all unmeasured aspects of the person.  If
so, if you use the coefficients b_1 to b_k estimated using Sample 1 on
non-estimation Sample 2, you'll obtain predicted values based on those
coefficients, but your predicted values will not include the
subject-specific effects (i.e., no b_0i estimates) because those were
obtained only for each unique person in the estimation sample.

Perhaps there is some way to do what you desire of which I am unaware
and, if so, I'd love to learn it.  But, my current knowledge indicates
what you want to do is not really appropriate for the fixed effects
model.

Sam

On Wed, Jun 12, 2013 at 12:31 PM, William Sankey <wsankey@gmail.com> wrote:
> Hi Statalist,
>
> I have two samples of the same data, my TEST_SAMPLE and
> VALIDATION_SAMPLE. I want to run a fixed effects model on my
> TEST_SAMPLE and collect the parameter estimates and apply them to the
> VALIDATION_SAMPLE. I believe I want to use the predict score command.
> After applying these coefficients to the VALIDATION_SAMPLE we want to
> compute the predicted value of my dependent variable as to compute the
> error.
>
> So far I believe I am on the right track with the following code:
>
> use TEST_SAMPLE
> xtset PROVIDER
> xtreg MARGIN {independent variables}, fe
>
> use VALIDATION_SAMPLE
> predict score
>
> At this point I'm not sure how to retrieve predicted values of the
> dependent variable to compute error. Also, if others have experience
> with this kind of procedure and used a different method they would
> recommend, I would appreciate it.
>
> Any insight would be greatly appreciated.
>
> Best,
> Will
> --
> William J. Sankey
> Johns Hopkins University
> MA Public Policy '12
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