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st: RE: zero-inflated analyses: when do you decide that is zero-inflated?


From   "Lachenbruch, Peter" <Peter.Lachenbruch@oregonstate.edu>
To   "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu>
Subject   st: RE: zero-inflated analyses: when do you decide that is zero-inflated?
Date   Mon, 15 Jul 2013 15:17:46 +0000

My view has been if you can justify the zeros being identified you can use the two-part model.  If you can't argue that, then zinp or zinb would be used.  If the data look Poisson, then you can just use poisson.  The usual test of variance*(n-1) divided by mean squared.

Peter A. Lachenbruch,
Professor (retired)
________________________________________
From: owner-statalist@hsphsun2.harvard.edu [owner-statalist@hsphsun2.harvard.edu] on behalf of Cris Dogaru (Oregon State University) [statamplus@gmail.com]
Sent: Monday, July 15, 2013 7:49 AM
To: statalist@hsphsun2.harvard.edu
Subject: st: zero-inflated analyses: when do you decide that is zero-inflated?

Dear Stata users,

I couldn't find an answer to this apparently simple question: how does
one decide that a distribution is zero-inflated, so that one can use
zero-inflated Poisson regression or zero-inflated negative binomial
regression?

More concrete: my outcome variable is number of positive skin prick
tests (done for 4 allergens, therefore the number has a range 0 to 4).
Here are the summary tables; is this zero-inflated?..


spt_number -- number of positive (wheal>3mm) STP
-----------------------------------------------------------
              |      Freq.    Percent      Valid       Cum.
--------------+--------------------------------------------
Valid   0     |        853      57.02      58.30      58.30
          1     |        286      19.12      19.55      77.85
          2     |        176      11.76      12.03      89.88
          3     |        105       7.02       7.18      97.06
          4     |         43        2.87       2.94     100.00
         Total |       1463      97.79     100.00
Missing .     |         33       2.21
Total         |       1496     100.00
-----------------------------------------------------------

. fsum spt_number

   Variable |        N     Mean       SD      Min      Max
------------+---------------------------------------------
 spt_number |     1463     0.77     1.10     0.00     4.00

Many thanks
Cristian Dogaru
ISPM, University of Bern
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