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Re: st: Re: Re: Estimating a model where the dependent variale is a ratio - Folllow up

From   Johannes Schoder <[email protected]>
To   [email protected]
Subject   Re: st: Re: Re: Estimating a model where the dependent variale is a ratio - Folllow up
Date   Fri, 04 Sep 2009 14:28:53 -0400

Thanks Martin,
Thanks Joseph,
Thanks Carlo,  your comments helped a lot!!

Just two things:
Concerning Josephs reply:
I tried the following for one year (e.g. year 2000):

glm A C, i (count) family (binomial B)
and I get the result my supervisor wanted me to get.
However, why are you suggesting xtgee?
I assume that you meant that I perform my estimation for several years.
I might try that later, too.

Concerning Carlos comment:
You think I should rather estimate a proportional hazard model (e.g. stcox or streg)? I mean you are right, I have data for each individual about its survival time, county of residence, county where it was diagnosed, age at diagnoses, etc... However I would like to see if in high volume counties (that are: counties where a lot of same cancer types i where detected) people (suffering from this cancer type i) survive longer.
So I think I have to group the data in the following way:
I have to calculate for each county the average survival time of individuals diagnosed with cancer type i
Or is this not necessary and I am loosing important information?

Again thanks a lot for your comments!

Joseph Coveney schrieb:
I wrote:

>From the SAS code that you've shown, your major professor seems to be fitting a
linear model.

I mistook, if I remember correctly now.  The PROC GENMOD syntax (MODEL A / B =
C;) that you showed *is* for a logistic model for which the corresponding Stata
command is (as was shown):

xtgee A C, i(country) family(binomial B)

Joseph Coveney

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