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st: RE: Analysis of Individual event data


From   "Nick Cox" <n.j.cox@durham.ac.uk>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: RE: Analysis of Individual event data
Date   Fri, 17 Jun 2005 17:56:08 +0100

After a -contract-. add a few pseudo-observations 
with zero frequency and then use -fillin-? 

Nick 
n.j.cox@durham.ac.uk 

Paul Seed
 
> I have a data set that consists of the dates of certain 
> arbitrary events
> (hospital appointments), together with various predictors; mainly
> date, numeric code for referring doctor (GP) & intervention 
> (pre/post ).
> I am interested in whether the intervention is associated 
> with a fall in
> the monthly rate of appointments, after adjusting for secular trend
> and clustering by GP.
> 
> One approach is to collapse the data & perform a Poisson or negative
> binomial regression.  However, the code needed for this is 
> surprisingly
> complex (see below), as I need to ensure that the practices with zero 
> frequencies in
> one time period are properly included, and the only way I 
> could see to do this
> was to tabulate, save the table as a matrix and then convert 
> it to a data set.
> 
> Two questions:
> 1) Is there a simpler way of collapsing the data without the 
> zero problem
> 2) Is there a way of analysing the data using it's present 
> structure (or 
> something like it)?
> 
> Any thought gratefully received.
> 
> 
> 
> .  use "westminster2", clear
> 
> . li  uniqid aptdate apttype pre_ post_ in 1/5
> 
>       +----------------------------------------------+
>       | uniqid     aptdate    apttype   pre_   post_ |
>       |----------------------------------------------|
>    1. |   6220   11 Apr 02   first vi      0       1 |
>    2. |   6159   12 Mar 02   first vi      0       1 |
>    3. |   6175   21 Mar 02   first vi      0       1 |
>    4. |   6210   09 Apr 02   first vi      0       1 |
>    5. |   6165   14 Mar 02   first vi      0       1 |
>       +----------------------------------------------+
> 
> tempname temp
> 
> 
>          tab refcode prepost if hosp == 1, matcell(temp) 
> matrow(gp_ref_cd)
> 
>          svmat temp, names(col)
>          svmat gp_ref_cd ,names(gp_ref_cd)
> 
>          keep c1 c2 gp_ref_cd
>          rename gp_ref_cd1 gp_ref_cd
>          drop if gp_ref_cd >=.
> 
>          reshape long c, i(gp_ref_cd) j(prepost)
>          rename c n_appt
>          gen post = prepost == 2
> 
>          svyset , psu(gp_ref_cd)
>          svynbreg n_appt post , irr
> 

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