Hi Maarten,
The model is trying to explain variations in annual hospital costs at the
individual patient level. We have various individual level variables such
as age, gender, and previous hospital use, but we also have a number of
variables that reflect the socio-economic characteristics of the area in
which the person lives. The addition of these attributed
need-for-health-care variables boosts the model's adjusted R-squared a
little but the boost is almost the same (at least to 4 decimal places)
whether all of them are included or just 12 are chosen on the basis of
researcher experience. Rather than use researcher experience to identify
the relevant variables, it would be good to have a slightly more formal
procedure.
Steve
-----Original Message-----
From: [email protected]
[mailto:[email protected]] On Behalf Of Maarten buis
Sent: 30 January 2009 16:55
To: [email protected]
Subject: RE: st: AW: estimation of series of OLS regressions based on
t-values from previous regression
--- sdm1 <[email protected]> wrote:
> I'm afraid that it will have to be done (considerably) more than once!
> If anyone could offer an idea of how to get started with a program,
> that would be much appreciated.
You seem to be aware that applying this method on that number of variables
will mean that your results cannot in any way be generalized outside your
data. Just out of curiosity, could you give a bit of substantive background
behind your problem, showing that generalizability is not of interest in
your case? It would be nice to have a real life example of an exception to
the rule that stepwise/datamining/datasnooping is evil.
-- Maarten
-----------------------------------------
Maarten L. Buis
Department of Social Research Methodology Vrije Universiteit Amsterdam
Boelelaan 1081
1081 HV Amsterdam
The Netherlands
visiting address:
Buitenveldertselaan 3 (Metropolitan), room N515
+31 20 5986715
http://home.fsw.vu.nl/m.buis/
-----------------------------------------
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