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st: RE: zero-inflated analyses: when do you decide that is zero-inflated?
From
"Lachenbruch, Peter" <[email protected]>
To
"[email protected]" <[email protected]>
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: [email protected] [[email protected]] on behalf of Cris Dogaru (Oregon State University) [[email protected]]
Sent: Monday, July 15, 2013 7:49 AM
To: [email protected]
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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