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st: RE: Poisson regression with score/scale as DV
From
Reinhardt Jan Dietrich <[email protected]>
To
"[email protected]" <[email protected]>
Subject
st: RE: Poisson regression with score/scale as DV
Date
Tue, 3 Apr 2012 08:07:13 +0000
You could use nbvargr to compare observed probabilities of your outcome with poisson probabilities ... However, I do not fully understand how you construct your outcome score ... Ordinal items should definitely not be summed up ... However, if you have something like (no problem, some problem, major problem ...) you could dichotomize each item so that 1 is indicative of any problem and then build a sum index which should be aprox. Poisson distributed...
Best
Jan
-----Original Message-----
From: [email protected] [mailto:[email protected]] On Behalf Of Clinton Thompson
Sent: Dienstag, 3. April 2012 09:59
To: [email protected]
Subject: st: Poisson regression with score/scale as DV
Hello All,
Based on Austin Nichol's July 2010 presentation on use of Poisson for
non-negative skewed variables
(http://www.stata.com/meeting/boston10/boston10_nichols.pdf) as well
as Bill Gould's Stata blog post about the same
(http://blog.stata.com/2011/08/22/use-poisson-rather-than-regress-tell-a-friend/),
I'm considering Poisson for a problem I have, albeit the dependent
variable is different enough from their examples that I'm unsure
whether Poisson is entirely appropriate. In my problem, the DV is a
"score" assigned to each subject based on their responses to several
component (ordinal scaled) questions. This variable is bound between
zero and 27 and the distribution of responses is decidedly non-normal
(pile-up of responses at the zero value). Any thoughts on whether
Poisson is still a good candidate or should I be considering other
approaches? And if Poisson is not the right way to go, any advice on
how to model this DV?
I'm using Stata/SE 11.2 for Windows.
Many Thanks,
Clint Thompson
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