[R] Ancova_non-normality of errors

[Yvonnick NOEL]

Hello Tobias,

I am not sure what your wt variable is: I suspect a 'weight'. If it is a nonnegative measure, then you want a positive density model, not a normal density in the first place. I think you should try a Gamma GLM, and look at a Gamma qqplot within each of your conditions. You could try the following:

M1 = glm(wt ~ pes + origin + gender + gender:pes, family=Gamma(link=identity))

M2 = glm(wt ~ pes + origin + gender + gender:pes, family=Gamma(link=log))

M3 = glm(wt ~ pes + origin + gender + gender:pes, family=Gamma(link=inverse))

and see whether one of them fit better, in terms of qqplot adjustment or comparative fit indicies (AIC, BIC,...).

HTH,

Yvonnick Noel, PhD
University of Brittany
France

> Message: 1
> Date: Sun, 04 May 2008 11:56:09 +0200
> From: Tobias Erik Reiners <Tobias.Reiners at bio.uni-giessen.de>
> Subject: [R] Ancova_non-normality of errors
> To: r-help at r-project.org
> Message-ID: <20080504115609.x1pgm2mgw0k0kooo at imap.stud.uni-giessen.de>
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>
> Hello Helpers,
>
> I have some problems with fitting the model for my data...
> -->my Literatur says (crawley testbook)=
> Non-normality of errors-->I get a banana shape Q-Q plot with opening  
> of banana downwards
>
> The goal of my analysis is to work out what effect the categorial  
> factors(origin, gender) on the relation between  
> log(wt)~log(pes)(-->Condition, fett ressource), have.
> Does the source(origin) of translocated animals have an affect on  
> performance(condition)in the new area?
> I have already a best fit model and it looks quite good (or not?see below).
>
> two slopes(gender difference)and 6 intercepts(3origin levels*2gender levels)
>
> lm(formula = log(wt) ~ log(pes) + origin + gender + gender:log(pes))