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Re: re; st: Pweight
Gao-- you might have missed this in the -help-. Notice the section
set off by ** **'s.
-Steve
"aweights, or analytic weights, are weights that are inversely
proportional to the variance of an observation; i.e., the
variance of the jth observation is assumed to be sigma^2/
w_j, where w_j are the weights. **Typically, the observations
represent averages and the weights are the number of
elements that gave rise to the average"**
On Sep 18, 2008, at 11:15 AM, Gao Liu wrote:
Thanks, Steve and Austin,
I did check the help for weight,but had not much idea which type of
weight, if any, is appropriate. It is my first time to deal with
weight option.
Austin's suggestion is great. I'll check how it works. Any other
suggestions will be welcome
Best
Gao
On Thu, Sep 18, 2008 at 10:22 AM, Steven Samuels
<[email protected]> wrote:
"Should we use the pweight option in the regression?"
It appears that Gao did not consult -help weight-, where there is
a clear
answer to his question.
-Steve
"Gao Liu" <[email protected]> wrote:
We are estimating the impact of an intervention on the practice of
health providers. One outcome measure is the ratio of metformin
prescribed to diabetic patients. This ratio is defined as the ratio
between the number of diabetic patients prescribed with
metformin and
the total number of diabetic patients treated by the provider.
We try
to examine whether metformin ratios are different for treatment
group
and unexposed group before and after the intervention date.
Xtgee is
used to estimate the impact of the intervention.
But there is a problem: the number of diabetic patients varies a
lot
from one provider to another. Some had only one or two diabetic
patients in a quarter, while others had more than 50. If a provider
has only 2 diabetic patients, one of whom was prescribed with
Metformin, then one patient's drop from being prescribed with
metformin would lead to a change of 50% in the metformin ratio. In
contrast, a health provider with 100 diabetic patients will have
very
stable metformin ratio. Thus, it is inappropriate to treat all
providers the same in the regression.
Should we use the pweight option in the regression? Or is there any
other better approach that works for this study? Thank you
Be
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