[R-sig-ME] Question about zero-inflated Poisson glmer

Thierry Onkelinx thierry.onkelinx at inbo.be
Tue Jun 28 13:39:37 CEST 2016

Dear Philipp,

I'm wondering if there is some kind of 'detection limit' in the dataset.
After looking at the data I get the feeling that all values below 10 are
set at zero.
The relation between the counts and the covariates a and b are not linear.
They have an optimum.
The proportion of zero's is not constant but varies with the covariates. So
you need to model that can handle that. Many models assume that the
zero-inflation is constant.

I'd settle for a set of two models: a logistic regression for the zero or
count and a negative binomial for the non-zero counts. A truncate negative
binomial distribution (that doesn't have values below 10) would be ideal.

Best regards,

ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature and
team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance
Kliniekstraat 25
1070 Anderlecht

To call in the statistician after the experiment is done may be no more
than asking him to perform a post-mortem examination: he may be able to say
what the experiment died of. ~ Sir Ronald Aylmer Fisher
The plural of anecdote is not data. ~ Roger Brinner
The combination of some data and an aching desire for an answer does not
ensure that a reasonable answer can be extracted from a given body of data.
~ John Tukey

2016-06-28 10:51 GMT+02:00 David Duffy <David.Duffy op qimrberghofer.edu.au>:

> On Tue, 28 Jun 2016, Philipp Singer wrote:
> You can find a sample of the data here:
>> https://www.dropbox.com/s/kqqxmc3wp225lug/r_sample.csv.gz?dl=1
>> You can think of the setting as popularity of items "y" inside stores
>> "id" explained by two features "a" and "b" whereas "a" is more of a control
>> covariate and I am interested in whether "b" has a positive impact.
> Probably not very helpful (what a horrible distribution y has), but
> library(ordinal)
> x$cats <- cut(x$y, c(-1,0,10,100,1000,20000))
> c1 <- clmm2(cats ~ a + (1|id), data=x)
> c2 <- clmm2(cats ~ a + b + (1|id), data=x)
> does run...
> Cheers, David Duffy.
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