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RE: st: cox model with shared frailty
From
Tracy Clegg <[email protected]>
To
[email protected]
Subject
RE: st: cox model with shared frailty
Date
Thu, 22 Apr 2010 11:30:08 +0100
Hi,
Thanks Maarten, I had already started looking around for other computers
which was my main option, I was just checking I wasn?t missing something
obvious!
Can I ask a probably naïve question. If I run the model on a small sample
and say end up with a model that includes just 2 significant predictors out
of a possible 5, would I just check the final model with the 2 predictors on
the full dataset or do I need to go through the model building process
again?
Many thanks for your suggestions,
Tracy
-----Original Message-----
From: [email protected]
[mailto:[email protected]] On Behalf Of Maarten buis
Sent: 22 April 2010 11:04
To: [email protected]
Subject: Re: st: cox model with shared frailty
--- On Thu, 22/4/10, Tracy Clegg wrote:
> Hi, I am having a few problems with running a cox
> propotional hazard model with a shared frailty.
> My problem is that it is taking around 12 hours to
> run a model with just one predictor, does anyone know
> how I can speed up the model? I am using STATA/SE version 11.
>
> In my data I have over 10,000 animals which are clustered
> into 1,662 herds with between 6 and 12 animals in each herd.
> To add a further complication I have 2 predictors which are
> time varying.
I can see why that is taking long. I would do two things:
1) build your model on a dataset that contains only a sample
of your total data. I would sample herds not animals. So
say the variable identifying the herd is called herd, then
I would start my .do-file with
use complete_data.dta, clear
set seed 12345
bys herd: gen u = runiform()
bys herd (u): replace u = sum(u)
keep if u < .25 // keep 25% of the herds
drop u
2) Look around your departement to see if some computers
are going to remain unused for some days (because of
vacation/conference/field work/etc.), and ask those persons
if you can use their computer to run your complete model on.
Hope this helps,
Maarten
--------------------------
Maarten L. Buis
Institut fuer Soziologie
Universitaet Tuebingen
Wilhelmstrasse 36
72074 Tuebingen
Germany
http://www.maartenbuis.nl
--------------------------
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