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

[Juan Pablo Edwards Molina]

Thanks Ben and Paul... By the way, that was what actually happened
after fitting the glm:
...huge Wald confidence intervals...(from glm FAQ).
I will take a look on that section of glm FAQ.
best,
Juan Edwards
Juan


On Wed, Dec 6, 2017 at 11:53 AM, Ben Bolker <bbolker at gmail.com> wrote:
>
>   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
>>
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