glm model with all zeros for one of the factor level

  Agreed. I added a section to the glmm FAQ giving guidance on how to to
this in the GLMM case:
http://bbolker.github.io/mixedmodels-misc/ecostats_chap.html#digression-complete-separation


On 17-12-06 09:36 AM, Paul Johnson wrote:

(This question is about GLMs rather than mixed models in R.)

I recommend reading up on separation in logistic regression, where
the proportion in any of the categories formed by the fixed effects
is exactly 1 or 0, so that a maximum likelihood estimate of the log
odds doesn't exists. The logistf package is the simplest way of
dealing with this in R.

Good luck, Paul


Sent from BlueMail<http://www.bluemail.me/r?b=11327> On 5 Dec 2017,
at 16:00, Juan Pablo Edwards Molina
<edwardsmolina at gmail.com<mailto:edwardsmolina at gmail.com>> wrote:

Dear List members:

I performed two independent experiments (CRD) to test if a whitefly
has preference to infect with a virus: potatos, tomatos or peppers
(target hosts, TH), wether if the virus was obtained from potato or
tomato (source hosts, SH). So I released 100 white flyes (previously
infected with the virus from one or other SH) inside cages
containing 10 plants of each TH (30 total). This is how the data
looks like:

exp  SH    TH    cage    tot  posit

1     tom    tom     1       10     4 1     tom    bat      1
10     3 1     tom    pep     1       10     0 1     bat    tom
2       10     1 1     bat    bat       2       10     2 1     bat
pep      2       10     0

2     tom    tom     3       10     6 2     tom    bat      3
10     4 2     tom    pep     3       10     0 2     bat    tom
4       10     4 2     bat    bat       4       10     0 2     bat
pep      4       10     0

The issue I found here  is that pepper was not infected at all,
however it was infected in another experiment without chance of TH
choice: i.e. I released infectious whiteflies inside cages
containing the same pepper genotyope and they present the typical
virus disease symptoms.

So, how should I consider modeling this data? Zero-inflated negative
binomial using the total plants as offset? Hurdle-model? Should I
remove the pepper level for the model?

Any help would be really helpful.

Juan Edwards