On 16/06/14 08:49, Åström, Jens wrote:
Hi,
Adding to what's already been said:
Just in case you're not aware of this, I think you have a typo in your model. Are you
looking for
glm(Count~Sex+Time+Behaviour+Sex*Time+Sex*Behaviour+Time*Behaviour,family=poisson)? By
the way, I think this could also be written
glm(Count~Sex+Time+Behaviour+Sex:Time+Sex:Behaviour+Time:Behaviour,family=poisson) or
simply glm(Count~+Sex*Time+Sex*Behaviour+Time*Behaviour,family=poisson). The
"*" means both main effects and all possible interactions.
FWIW, glm(Count~(Sex +Time+Behaviour)^2,family=poisson) will also work:
it expands to the main effects and first order interactions.
(oh, and the advice I've seen is don't use Wald tests: they are
conservative because they assume the other parameters are fixed at their
MLEs, so ignore any uncertainty in them. Use likelihood ratio tests instead)
Bob
Also, you should probably look into the issue of overdispersion. Overdispersion
is very common in ecological count data and basically means that you have more
variation in your data than the Poisson distribution assumes. This typically
leads to anti-consevative p-values, i.e. too small p-values, and needs to be
accounted for.
Read more about it and potential solutions here: http://glmm.wikidot.com/faq
Good luck,
Jens
--
Message: 1
Date: Sat, 14 Jun 2014 18:55:44 -0700 (PDT)
From: Angel
To: r-sig-ecology@r-project.org
Subject: Re: [R-sig-eco] Question about GLM post hoc and chi square
Message-ID:
Content-Type: text/plain
You are able to obtain Chi squared values by using a wald chi square post hoc
test. To do this you can use the aod package, function wald.test. This function
is perfect for generalised linear models using poisson distribution.
Also, as long as you have got
interaction terms in your results from GLM, you could get the wald chi square
(and an associated p-value) for these terms, hence giving you the table which
you are after.
If this response is not clear enough, I can post some example (I am not sure of
the etiquette)
AA.
Date: Fri, 13 Jun 2014 18:07:27 -0700
From: ml-node+s471788n757894...@n2.nabble.com
To: alexander.angelo...@hotmail.com
Subject: Question about GLM post hoc and chi square
Dear all,
I am making an analysis using a GLM using three explanatory variables and a
response variable. I need to obtain a table similar to this one,
http://postimg.org/image/5sau79wlt/r
nevertheless, I have not been able to do it. I am having a hard time
specially getting the chi square values. I would like to know how to obatin
them.
I also would like to know what function could help me to make ad hoc
comparisons for single variables and interactions.
If any of you knows how to do both estimations, I would really appreciate
it.
All the best!!!
This is my script
a=read.table("ricis3.txt",header=T)
attach(a)
model7=glm(Count~Sex+Time+Behaviour+Sex*Time+Sex*Behaviour+Time+Behaviour*Sex,family=poisson)
summary(model7)
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--
Bob O'Hara
Biodiversity and Climate Research Centre
Senckenberganlage 25
D-60325 Frankfurt am Main,
Germany
Tel: +49 69 7542 1863
Mobile: +49 1515 888 5440
WWW: http://www.bik-f.de/root/index.php?page_id=219
Blog: http://blogs.nature.com/boboh
Journal of Negative Results - EEB: www.jnr-eeb.org
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