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Re: st: RE: Analyse variables used in a regression


From   Nick Cox <njcoxstata@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: RE: Analyse variables used in a regression
Date   Wed, 2 Jan 2013 18:30:07 +0000

See also

SJ-7-2  dm0030  . . . . . . . . . .  Stata tip 44: Get a handle on your sample
        . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  B. Jann
        Q2/07   SJ 7(2):266--267                                 (no commands)
        tip on how to keep track of the observations that make
        up your estimation sample

which is accessible to all at

<http://www.stata-journal.com/sjpdf.html?articlenum=dm0030>

Nick

On Wed, Jan 2, 2013 at 5:19 PM, Jacobs, David
<jacobs.184@sociology.osu.edu> wrote:

> The easiest way to deal with this is to run a regression; then in subsequent commends use -, if e(sample)- thereafter.  If you need a more permanent approach (since -e(sample)- is recomputed after each run) use -generate presence=e(sample), which will produce a dummy coded one for all cases in the prior regression model and zero otherwise.

Claude Francoeur

> The dataset I am using contains several  missing values. What would be the proper command(s) to analyse the data actually used in my regression. For example, I would like to produce descriptive tables to see how the subset that is used to perfom the regression is distributed among countries and industries.

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