[R-sig-eco] Question about GLM post hoc and chi square (Angel)

[Åström, Jens]

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.

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 <alexander.angeloski at hotmail.com>
To: r-sig-ecology at r-project.org
Subject: Re: [R-sig-eco] Question about GLM post hoc and chi square
Message-ID: <BLU174-W408EBBB0F91199F57E4D90F2170 at phx.gbl>
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+s471788n7578944h7 at n2.nabble.com
To: alexander.angeloski at 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)