--- Ashwin Ananthakrishnan <[email protected]> wrote:
> I am currently using Stata 9.2. My analysis involves
> logistic regression of a dichotomous outcome (dead /
> alive) across various predictors. My main predictor of
> interest is hospital type (Small, medium, big). How do
> I adjust for clustering within each type of hospital?
If I would do a control for clustering than I would
control for clustering within hospital, not within type
of hospital.
> The largest of the 'big' hospitals may contribute more
> patients to the analysis than the smaller of the 'big'
> hospitals. Do I need to adjust for this phenomenon?
> i.e. if we hypothesize that larger hospitals have
> better outcomes, isn't it appropriate that the larger
> of the big hospitals contribute more patients and
> hence have a larger weight?
>
> Or do I need to adjust for this? and how do I do it?
Differences in size of groups influence the standard
errors. Generally speaking: an odds ratio comparing
two large groups will have a smaller standard error
than an odds ratio comparing a large and a small
group, which turn will have a smaller standard error
than the odds ratio comparing two small groups. This
is exactly as it should be (more data --> less
uncertainty --> smaller standard error), so there is
no need for any adjustement here.
Hope this helps,
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 Z434
+31 20 5986715
http://home.fsw.vu.nl/m.buis/
-----------------------------------------
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