--- Henry <[email protected]> wrote:
> Salah, I am using secondary data from a primary care database. This
> contains patient details -medical, therapy and demoraphic
> information. In this case, i guess i will have to do some matching.
> Not all patients in the database have the outcome of interest and
> thus in order to use classical logistic regression models to
> evaluate risk of outcome with exposure allowing for possible
> conounders , we need to find controls as close to the cases as much
> as possible.
Matching techniques and `classical logistic regression' both control
for meausured confounders, and both require that the model is correctly
specified. I never understood the advantage matching/reweighting
techniques over multiple regression techniques. I got the distinct
impression that in many applied studies the matching/reweighting
technique is believed to solve much more problems than is actually the
case, though I probably have to reread (Nichols 2007) when I have time.
-- Maarten
Austin Nichols (2007) Causal inference with observational data, The
Stata Journal, 7(4): 507--541.
http://www.stata-journal.com/article.html?article=st0136
-----------------------------------------
Maarten L. Buis
Department of Social Research Methodology
Vrije Universiteit Amsterdam
Boelelaan 1081
1081 HV Amsterdam
The Netherlands
visiting address:
Buitenveldertselaan 3 (Metropolitan), room Z434
+31 20 5986715
http://home.fsw.vu.nl/m.buis/
-----------------------------------------
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