...
Yes, but remember the result would be college males relative to no
college females. Also, you are assuming that there is no multiplicative
interaction between college and sex. In other words, the sex effect is
the same regardless of whether or not you went to college (and the
college effect is the same regardless of sex).
You should probably check that by fitting i.gender*i.education.
______________________________________________
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) 9224-2701
Fax: (08) 9224 8009
email: [email protected]
http://myprofile.cos.com/mccaul
http://www.researcherid.com/rid/B-8751-2008
______________________________________________
If you live to be one hundred, you've got it made.
Very few people die past that age - George Burns
-----Original Message-----
From: [email protected]
[mailto:[email protected]] On Behalf Of Data
Analytics Corp.
Sent: Wednesday, 24 June 2009 9:18 AM
To: Stata Listserve
Subject: st: Interpreting Poisson output
Hi Stata,
I have a simple question about interpreting Poisson output. Suppose I
have a simple model with counts of newspapers read as the dependent
variable and gender and education as the independent variables. The two
independent variables are both dummy coded so gender is just 1 = male/0
= female and education is just 1 = college/0 = no college. If I use
poisson count gender education, irr
I get reasonable answers. The gender coefficient exponentiated tells me
the change in the count for males relative to females. Similarly for
education. What if I want to know males who went to college? Do I just
exponentiate the sum of the two coefficients? I think so. Are there
any things to watch for?
Thanks,
Walt
--
________________________
Walter R. Paczkowski, Ph.D.
Data Analytics Corp.
44 Hamilton Lane
Plainsboro, NJ 08536
________________________
(V) 609-936-8999
(F) 609-936-3733
[email protected]
www.dataanalyticscorp.com
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