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RE: st: RE: FWD: poisson regression on aggrgregated data


From   [Redacted]
To   <statalist@hsphsun2.harvard.edu>
Subject   RE: st: RE: FWD: poisson regression on aggrgregated data
Date   Mon, 9 Feb 2009 12:30:04 +0000

Dear Kieran
 
 
No I am not modeling mortality rates, I am modeling the incident of experiencing an event by patients using these 2 covariates:
 
Year_start (year of starting treatment): 1997,1998,1999,...,2008
time_since_start:0_1, 1_2, 2_3,...,Max
 
My original data was not in aggregated form, and patients experienced the event (1) or not (0). Then I splitted the follow up time in one year periods and coded year_start,1997 as 1 and 1998+ as 2 and time_since start ,0_1 as 1, 1_2 as 2 and 2+ as 3. then aggregated data using these coded covariates:
 
strate year_start_cat  time_since_start_cat
 
saved the output, and used poisson on _D (count of events in each group)-created by strate-, above 2 coded covariates (year_startcat, time_since_startcat) and the exposure that would be created aggregated follow up time _Y ,and then predicted number of events and incident rates in each group using predict.
 
Now I would like to use the coefficients of this fitted poisson model and have the predicted incident rates in disaggregated data (for year_start and time_since_start before grouping them)
 
for example the incident rate for  year_start=2003 (whitch has been coded as year_startcat=2) and year_since_start=3_4 (which has been coded as year__since_startcat=3) 
 
Would it be correct if I use the same predicted incident rate from poisson on grouped data (1998+ and 2+) and use it for above example or each case in this group or in this case more events than really is will be predicted? 
 
Many thanks,
Shell


> Subject: st: RE: FWD: poisson regression on aggrgregated data
> Date: Mon, 9 Feb 2009 04:09:31 +0900
> From: kamccaul@meddent.uwa.edu.au
> To: statalist@hsphsun2.harvard.edu
> 
> .
> 
> It's not clear from this description what you are modelling. Is it
> mortality rates?
> Second, when you say that you have used aggregated data, is this data
> that you have aggregated or was the data already in aggregated form?
> 
> 
> 
> ______________________________________________
> Kieran McCaul MPH PhD
> WA Centre for Health & Ageing (M573)
> University of Western Australia
> Level 6, Ainslie House
> 48 Murray St
> Perth 6000
> Phone: (08) 9224-2140
> Fax: (08) 9224 8009
> email: kamccaul@meddent.uwa.edu.au
> http://myprofile.cos.com/mccaul 
> http://www.researcherid.com/rid/B-8751-2008
> ______________________________________________
> The fact that no one understands you doesn't make you an artist.
> 
> -----Original Message-----
> From: owner-statalist@hsphsun2.harvard.edu
> [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Martin Weiss
> Sent: Sunday, 8 February 2009 7:55 PM
> To: statalist@hsphsun2.harvard.edu
> Subject: st: FWD: poisson regression on aggrgregated data
> 
> <>
> 
> Dear [Redacted],
> 
> short answer: I do not know! BTW, it is not clear to me why you want to
> tap 
> only my wisdom when you can have the entire list. So I am forwarding
> this 
> topic to the list for you...
> 
> 
> HTH
> Martin
> _______________________
> 
> 
> Dear Martin
> 
> I would like to ask the following question.
> 
> I have used poisson regression on aggrgregated data with 2 covariates
> (in a 
> cohort of HIV positive patients)
> 
> 1.year of starting 3+ antiretroviral treatment (1997, 1998+)
> 2.time since starting 3+antiretrovirals (0-1, 1-2, 2+)
> 
> and I have predicted incident rates in this aggregated data using
> predict 
> option after the poisson model.
> 
> Now my question is if I want to have predicted incident rates for
> patients 
> starting 3+ arvs at 2000 and time since starting 3+ arvs , 3_4 years
> is it correct to use the same predicted incident rate obtained for 
> aggregated data and in this example use predicted incident rate for
> 1998+ 
> and 2+?
> 
> It would be greatly appreciated if you could answer my question, Please
> let 
> me know if you would like me to provide more details.
> 
> Thank you very much in advance,
> 
> Kind regards,
> Shell
> 
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