On Thu, 7 Nov 2013, sv.j...@yahoo.ca wrote:
Hello,
I have count data for 4 groups, 2 of which have a large number of zeroes
and are overdispersed, and the other 2 underdispersed with no zeroes.
Are you sure that it's really underdispersion in addition to the lack of
zeros? It could also be that due to the missing zeros, there is less
dispersion.
I have two questions about model fitting, which I am quite new to, and
have been using mostly the pscl package.
1 - How do I deal with underdispersion? Almost all the published and
online advice is regarding overdispersion, and neither the Poisson nor
negative binomial distribution seem appropriate. The COM Poisson comes
up sometimes as a suggestion, but it's not clear to me how I can use
this, explain my choice of it, or what information I would report for
publication purposes.
There are (at least) two packages on CRAN: compoisson and ComPoissonReg
which support this.
However, I would check first whether this is really needed or maybe a
zero-truncated Poisson model is already sufficient.
The package "countreg" on R-Forge
(https://R-Forge.R-project.org/R/?group_id=522) has a function zerotrunc()
which is essentially the same code that hurdle() in "pscl" uses. So it
should be easy to use for you.
2 - For the overdispersed data with lots of zeroes, I've tried
zero-inflated Poisson and NegBin and hurdle models, and used the Vuong
test to compare. However, I get equal fit for two candidate models that
produce quite different coefficient estimates for my predictor
variables, and hence different p values. I am unsure how to proceed in
choosing one of these models, and how I would justify one over the other
given that the Vuong test seems not to discriminate.
Is it just zero-inflated vs. hurdle or also differences in the regressors?
If the former: zero-inflated and hurdle models are parametrized
differently but often lead to similar fits. But the former has a count
part plus a zero-inlation part whereas the latter as a zero-truncated
count part and a zero hurdle.
If the regressors are different, then it's probably a subject-matter
decision.
hth,
Z
Thank you and any advice would be much appreciated.
Mo
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