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RE: st: Multilevel modelling of survival data


From   hind sbihi <sbihi@interchange.ubc.ca>
To   statalist@hsphsun2.harvard.edu
Subject   RE: st: Multilevel modelling of survival data
Date   Mon, 16 Mar 2009 11:39:47 -0700

Murray, 

Val nous attendra a son bureau a 13h45.
A+


-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu
[mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Justin B Echouffo
Tcheugui
Sent: Monday, March 16, 2009 9:17 AM
To: statalist@hsphsun2.harvard.edu
Subject: RE: st: Multilevel modelling of survival data

Dear Marteen, 
I tried the command stcox with the option -shared () as you advised. As
you can see below I am not having the desired output 
xi: stcox  i.randomgp, shared(clinic)
i.randomgp   _Irandomgp_0-1     (naturally coded; _Irandomgp_0 omitted)

failure _d:  event
analysis time _t:  followup_time

Fitting comparison Cox model:

Estimating frailty variance: 
numerical derivatives are approximate flat or discontinuous region
encountered 
Iteration 0:   log profile likelihood = -2482.4152 
could not calculate numerical derivatives flat or discontinuous region
encountered r (430);

I tried adding the option - difficult, hoping that it will help but it
did not 
xi: stcox  i.randomgp, shared(practice) difficult
i.randomgp       _Irandomgp_0-1     (naturally coded; _Irandomgp_0
omitted)

failure _d:  event
analysis time _t:  followup_time

Fitting comparison Cox model:

Estimating frailty variance:
numerical derivatives are approximate flat or discontinuous region
encountered
Iteration 0:   log profile likelihood = -2482.4152  
could not calculate numerical derivatives flat or discontinuous region
encountered r(430);

Could you please advise on this?  
Many thanks 
Justin B. 

-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu
[mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Maarten buis
Sent: 16 March 2009 10:58
To: stata list
Subject: RE: st: Multilevel modelling of survival data


--- On Mon, 16/3/09, Justin B Echouffo Tcheugui wrote:
> > in this case the option - cluster() in this case does
> > not fit the clinic into the model as a random
> > intercept 

--- On Mon, 16/3/09, Maarten buis wrote: 
> That is correct. 

A point on terminology again: When discussing the 
distrinction between these models, the models estimated 
with the -cluster()- option are sometimes known as 
population averaged models, while the random intercept 
models are sometimes known as individual specific models.

-- Maarten

-----------------------------------------
Maarten L. Buis
Institut fuer Soziologie
Universitaet Tuebingen
Wilhelmstrasse 36
72074 Tuebingen
Germany

http://home.fsw.vu.nl/m.buis/
-----------------------------------------





      

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