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Re: st: Reasons for varying OLS coefficients across different sub-samples.


From   Nick Cox <njcoxstata@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Reasons for varying OLS coefficients across different sub-samples.
Date   Mon, 18 Jul 2011 15:34:54 -0500

There are many possible answers to this. One is that the variability
you are observing is really interesting scientifically and/or
practically, so that this is not a problem. Another is that you should
consider using some transformed scale for some or all of your
variables. Another is to consider e.g quantile regression.

Note, however, that -robust- options don't necessarily confer
protection against outliers. The term "robust", like many others, is
used in varying ways across statistical science.

Nick

On Mon, Jul 18, 2011 at 3:21 PM, Gupta, Sumedha <sugupta@iupui.edu> wrote:
> Dear All,
>
> I am running some OLS regressions on survey data (using svy) and seem to get very different results across different random sub-samples I draw from the sample. I believe two common reasons for this could be heteroscedasticity and outliers. Svy does not allow robust option after reg. Is there another way to test for why I am getting such different results for different sub-samples and more importantly is there a way of getting more robust results?
>

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