Thanks Martin,
Thanks Joseph,
Thanks Carlo, your comments helped a lot!!
Just two things:
A.
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.
B.
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!
Best,
Johannes
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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