Thanks for the advice on Q1.
I do stset for patient-level data, but most quality assurance data in
medical practice is reported at unit-level. Panel data approaches are useful
for analysing such data, offsetting by a variety of measures to account for
unit-level casemix...
Any thoughts on Q2?
MM
-----Original Message-----
From: [email protected]
[mailto:[email protected]] On Behalf Of Martin Weiss
Sent: Sunday, 12 April 2009 9:52 a.m.
To: [email protected]
Subject: Re: Corrected repost: Two general questions about xt commmands and
re / fe
<>
BTW, just out of curiosity: Your problem sounds very much like a survival
analysis issue. Have you considered -stset-ting?
HTH
Martin
_______________________
----- Original Message -----
From: "Mark Marshall" <[email protected]>
To: <[email protected]>
Sent: Saturday, April 11, 2009 11:37 PM
Subject: Corrected repost: Two general questions about xt commmands and re /
fe
> Hi
>
> I am using Stata 9.2 on windows.
>
> I am fitting an xtpoisson model to unbalanced panel data (n counts of
> death
> over T months), with a grouping variable called unit that signifies the
> ICU
> where the data come from. E.g
>
> obs_rrt T unit
> 0 5 4
> 3 6 4
> 2 7 4
> 4 8 4
> 3 9 4
> 1 10 4
> 3 2 3
> 1 3 3
> 1 4 3
> 1 5 3
> 0 6 3
> 1 7 3
>
> Question 1.
>
> When I specify
>
> tis T
>
> my understanding is that this does not explicitly model T in the model (I
> want to model the death rate in relationship to time, amongst other
> things),
> and I would have to specify T in the command line to do this. Is this
> correct?
>
> Question 2.
>
> I would like to specify T and some other exposure covariates as fixed
> effects, and unit as a random effect in the model. If I specify all of
> these
> as independent variables in the command line, and then use the re option,
> how can I tell which is modelled as fixed, and which is modelled as
> random?
>
> Thanks,
>
> Mark Marshall
>
>
>
>
>
>
>
>
>
> *
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>
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