Thank you Kieran
I think The rates will be the same in below question but the incidents of course will be lower. I found the predictions for each year this time by using the whole data (strate year_since_start and year_start) and then coding them in the way that I want and fitting the poisson on the coded data. Before this I just had used the coded data(strate year_since_start_cat year_start_cat)
Thanks again for your time and your complete respond
Shell
----------------------------------------
> From: [Redacted]
> To: [email protected]
> Subject: RE: st: RE: FWD: poisson regression on aggrgregated data
> Date: Tue, 10 Feb 2009 01:32:28 +0000
>
>
>
>
> Thank you very much Kieran for your response. I will difinetly read your paper.
>
> Now my question is if the predicted rate in my final poisson model for example for time_since_start_cat=3 and year_start_cat=2 is 0.076 or 76 per 1000 person years , what will be the predicted rate :
>
> for example for year_start=2003 (whitch has been coded as year_start_cat=2) and year_since_start=3_4 (which has been coded
>> as year__since_start_cat=3)
>
> Will it be 0.076 person years? If not how can I have the predicted rate for ungrouped data using my poisson model.
>
>
>
> Many thanks again,
> Shell
>
>
>
>> Subject: RE: st: RE: FWD: poisson regression on aggrgregated data
>> Date: Tue, 10 Feb 2009 06:28:51 +0900
>> From: [email protected]
>> To: [email protected]
>>
>> OK, I see.
>>
>> You have the year that treatment started: 1997,1998,1999,...,2008
>> which you have coded as:
>> year_start_cat = 1 if year_start=1997 and
>> year_start_cat = 2 if year_start=1998,1999,...,2008
>>
>> You have time since the treatment started (time_since_start):0_1, 1_2,
>> 2_3,...,Max
>> coded as:
>> time_since_start_cat = 1 if time_since start = 0_1 .
>> time_since_start_cat = 2 if time_since start = 1_2
>> time_since_start_cat = 3 if time_since start = 2_3,...,Max
>>
>> Then you modelled the incidence rates using these covariates and now you
>> want to predict the rates in each of the calendar years that treatment
>> started (1997,1998,1999,...,2008) and in each of the years since
>> treatment started (0_1, 1_2, 2_3,...,Max).
>>
>> Your model is assuming that the rate in the treatment years 1998 to 2008
>> is the same. Similarly, it is assuming that after two years of
>> follow-up have elapsed, the rate is the same; constant with time since
>> treatment started. In fact, it is assuming that this constant rate is
>> the same for all treatment years, 1998 to 2008.
>>
>> If these assumptions are correct, then you could use the model to
>> predict the rates, but you would need to provide some evidence that they
>> are correct.
>>
>> If you have sufficient data, you could use -strate- to generate the
>> rates for year_start and time_since start to see if your assumptions are
>> essentially correct.
>>
>> strate year_start time_since start
>>
>> This would give you the annual incidence rates since treatment started
>> and you could graph these for each calendar year. I did something
>> similar to this in a study of second primary melanoma rates:
>> McCaul et al. The incidence of second primary invasive melanoma in
>> Queensland, 1982-2003. Cancer Causes Control 2008; 19(5):451-8.
>>
>> Alternately, you could go back to your original data and use
>> Kaplan-Meier to generate hazard curves by calendar year of treatment.
>> These should be constant three or more years after treatment and they
>> should be similar for 1998 through to 2008.
>>
>> ______________________________________________
>> 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: [email protected]
>> 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: [email protected]
>> [mailto:[email protected]] On Behalf Of [Redacted]
>> Sent: Monday, 9 February 2009 9:30 PM
>> To: [email protected]
>> Subject: RE: st: RE: FWD: poisson regression on aggrgregated data
>>
>> 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: [email protected]
>>> To: [email protected]
>>>
>>> .
>>>
>>> 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: [email protected]
>>> 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: [email protected]
>>> [mailto:[email protected]] On Behalf Of Martin
>> Weiss
>>> Sent: Sunday, 8 February 2009 7:55 PM
>>> To: [email protected]
>>> 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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