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st: RE: nbreg proc genmod equivalency


From   "Kieran McCaul" <kamccaul@meddent.uwa.edu.au>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: RE: nbreg proc genmod equivalency
Date   Fri, 28 Nov 2008 06:05:12 +0900

Hi Victor,

You might get a response I fyou sent the SAS code that generated this
output and then the Stata code that you are trying to use.

Kieran

______________________________________________
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 
_______________________________________________
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 Victor M.
Enciso M.
Sent: Thursday, 27 November 2008 9:04 PM
To: statalist@hsphsun2.harvard.edu
Subject: st: nbreg proc genmod equivalency

Hi everybody,

I'm doing a negative binomial regression using Proc Genmod on SAS
where this is part of the output


Parameter   DF    Estimate       Error           Limits       Square
Pr > ChiSq

TRT   1      1     -0.2397      0.1102     -0.4557   -0.0237   4.73
0.0296
TRT   2      0      0.0000      0.0000      0.0000    0.0000
Dispersion   1      0.1268      0.0315      0.0651    0.1885

NOTE: The negative binomial dispersion parameter was estimated by
maximum likelihood.


                     LR Statistics For Type 1 Analysis
                          2*Log                 Chi-
          Source       Likelihood        DF     Square    Pr > ChiS

          Intercept     5189.2817
          PAIR          5253.0473        34      63.77        0.0015
          TRT           5257.5618         1       4.51        0.0336


                      LR Statistics For Type 3 Analysis

                                   Chi-
          Source           DF     Square    Pr > ChiSq

           PAIR             34      65.03        0.0011
           TRT               1       4.51        0.0336


I'm trying to reproduce this analysis in Stata but I don't know how to
get the Type 1 and Type 3 Statistics. Anybody knows how to do this?

Another question is why are the p-values of the contrast of tratment 1
wrt to treatment 2 (0.0296) and the one given for TRT (0.0336)
different?

Thank you very much.

Victor Enciso



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