[R-sig-ME] glm model with all zeros for one of the factor level

[Paul Johnson]

(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


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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

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