[R-sig-ME] Offset vs fixed factor in a mixed poisson model

[Highland Statistics Ltd]

On 17/01/2013 07:00, r-sig-mixed-models-request at r-project.org wrote:
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>     1. Offset vs fixed factor in a mixed poisson model
>        (v_coudrain at voila.fr)
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> Message: 1
> Date: Thu, 17 Jan 2013 11:08:51 +0100 (CET)
> From: v_coudrain at voila.fr
> To: r-sig-mixed-models at r-project.org
> Subject: [R-sig-ME] Offset vs fixed factor in a mixed poisson model
> Message-ID: <436652575.252611358417331707.JavaMail.www at wwinf7130>
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> Dear subscribers,

Valerie,
>   
> I am tested the effect of a factor on a count variable using a poisson mixed model. I know that my response variable is linearly influenced by an other variable so
Keep in mind that you are using an exponential relationship in a 
GLM...at least if you use the log link.
> that I would like to remove the effect of this second variable to see the true effect of my factor. In an anova, it is usual to enter the covariable first in the model and
> use a sequential test (type I SS). However I am a bit confused how to control for this covariable in my mixed-poisson model. If I just give the covariable as an
> additional fixed variable, my factor is highly significant. If I put it instead as an offset, the factor is not significant at all. I think that it is better to use offset, but I must

If you use a covariate as an offset then you essentially saying: double 
the value of the variable used for the offset, double the numbers 
(strictly speaking: the expected value). Quite often sampling effort is 
used as an offset as it is not really interesting to model a 
cause-effect relationship between sampling effort and your response.

If you have a model with:

glm(y ~ x, family = poisson)
glm(y ~ x + offset(z), family = poisson)

and x is significant in the first model...but not in the second, then 
either the offset explains most variation, or x and the offset are 
highly correlated? Plot x versus z...and plot x versus log(z)...

Alain


> admit that the underlying "theory" is not clear for me. I was also wondering if we can specify multiple offsets and if there was some "rule of thumb" in the maximal
> number that can be included. Thank you very much.
> Best,
> Valerie
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> End of R-sig-mixed-models Digest, Vol 73, Issue 21
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-- 

Dr. Alain F. Zuur
First author of:

1. Analysing Ecological Data (2007).
Zuur, AF, Ieno, EN and Smith, GM. Springer. 680 p.
URL: www.springer.com/0-387-45967-7


2. Mixed effects models and extensions in ecology with R. (2009).
Zuur, AF, Ieno, EN, Walker, N, Saveliev, AA, and Smith, GM. Springer.
http://www.springer.com/life+sci/ecology/book/978-0-387-87457-9


3. A Beginner's Guide to R (2009).
Zuur, AF, Ieno, EN, Meesters, EHWG. Springer
http://www.springer.com/statistics/computational/book/978-0-387-93836-3


4. Zero Inflated Models and Generalized Linear Mixed Models with R. (2012) Zuur, Saveliev, Ieno.
http://www.highstat.com/book4.htm

Other books: http://www.highstat.com/books.htm


Statistical consultancy, courses, data analysis and software
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