Thanks, Eric,
the treatment was a dummy, so I don't need to tabulate that -- but I
would need to tabulate my cluster id, to have interactions if I want
to put all that into one regression. However, that would mean
thousands of new variables, not very elegant. I think I'll stick to
'regression of residuals on residuals' as mentioned above, if nothing
else comes up.
Thanks again,
Laszlo
On Tue, Aug 25, 2009 at 11:59 AM, DE SOUZA
Eric<[email protected]> wrote:
> How is your treatment dummy defined?
> If it is a categorical variable: 1, 2 ,3, etc, define a set of dummies by -tab(var), gen(var)
> Example:
> . webuse grunfeld
>
> . tab(company), gen(company)
>
> . reg invest mvalue kstock company1-company9
> .......
> ------------------------------------------------------------------------------
> invest | Coef. Std. Err. t P>|t| [95% Conf. Interval]
> -------------+----------------------------------------------------------------
> mvalue | .1101238 .0118567 9.29 0.000 .0867345 .1335131
> kstock | .3100653 .0173545 17.87 0.000 .2758308 .3442999
> company1 | -63.72884 50.33023 -1.27 0.207 -163.0134 35.55572
> company2 | 108.4737 26.95322 4.02 0.000 55.30405 161.6433
> company3 | -229.004 26.51076 -8.64 0.000 -281.3008 -176.7072
> company4 | -21.24145 18.04916 -1.18 0.241 -56.84635 14.36346
> company5 | -108.049 18.43201 -5.86 0.000 -144.4091 -71.68883
> company6 | -16.59345 17.12189 -0.97 0.334 -50.36917 17.18227
> company7 | -59.98563 17.44425 -3.44 0.001 -94.39725 -25.57401
> company8 | -50.97781 17.9877 -2.83 0.005 -86.46148 -15.49414
> company9 | -80.65443 17.37635 -4.64 0.000 -114.9321 -46.37675
> _cons | -6.567843 11.82689 -0.56 0.579 -29.89831 16.76262
> ------------------------------------------------------------------------------
>
> Eric
>
>
>
> Eric de Souza
> College of Europe
> Brugge (Bruges), Belgium
> http://www.coleurope.eu
>
> -----Original Message-----
> From: [email protected] [mailto:[email protected]] On Behalf Of László Sándor
> Sent: 25 August 2009 17:48
> To: [email protected]
> Subject: Re: st: AW: how to get slopes by clusters in a linear regression
>
> Thank you, Martin!
>
> I don't see how this could be used to estimate the model in a single command -- statsby still seem to break down the regression by clusters, without the intercluster restrictions on the controls/covariates.
>
> However, this led me to try to apply the Frisch-Waugh-Lowell theorem:
> I estimate the univariate regression of outcome on treatment by each cluster, I must only use the residuals for both after regressing them on the set of controls.
>
> If there is no other way, this seems to be doable.
>
> Thanks again!
>
> Laszlo
>
> On Tue, Aug 25, 2009 at 11:23 AM, Martin Weiss<[email protected]> wrote:
>>
>> <>
>>
>>
>> ******
>> h statsby
>> ******
>>
>>
>> HTH
>> Martin
>>
>>
>> -----Ursprüngliche Nachricht-----
>> Von: [email protected]
>> [mailto:[email protected]] Im Auftrag von László
>> Sándor
>> Gesendet: Dienstag, 25. August 2009 17:20
>> An: [email protected]
>> Betreff: st: how to get slopes by clusters in a linear regression
>>
>> Dear Fellow Statalisters,
>>
>> I want to extend a fixed-effects-type model to allow for different
>> coefficients on a variable (actually a treatment dummy) by each
>> cluster I have. The richness of my data would allow for that. However,
>> I did not find a way to do it in Stata that would report (and collect)
>> the coefficients themselves. -xtmixed- doesn't seem to do so. I would
>> like to restrict the coefficients on controls to be equal across
>> clusters, so estimation by cluster is not a solution either.
>>
>> If there were a way that could collect the slopes to a single new
>> variable (with the same value for observations in the same cluster,
>> naturally), that would be the best. It would be great if I did not
>> need to introduce all the 1438 cluster-indicator variables and
>> interactions myself, and collect the coefficients.
>>
>> Thank you for any guidance in advance!
>>
>> Laszlo
>> *
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>>
>>
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>>
>
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