[R] improvement of Ancova analysis

From: Tobias Erik Reiners <Tobias.Reiners_at_bio.uni-giessen.de>
Date: Sun, 04 May 2008 04:00:16 +0200


Dear Helpers,

I just started working with R and I'm a bit overloaded with information.

My data is from marsupials reindroduced in a area. I have weight(wt), hind foot
lenghts(pes) as continues variables and origin and gender as categorial. condition is just the residuals i took from the model.

> names(dat1)

[1] "wt" "pes" "origin" "gender" "condition"

my model after model simplification so far: model1<-lm(log(wt)~log(pes)+origin+gender+gender:log(pes)) -->six intercepts and two slopes

the problem is i have some things I can't include in my analysis: 1.Very different sample sizes for each of the treatments
> tapply(log(wt),origin,length)

captive site wild

     119 149 19
2.Substantial differences in the range of values taken by the covariate (leg length) between treatments
> tapply(pes,origin,var)

  captive site wild
82.43601 71.44442 60.42544
> tapply(pes,origin,mean)

  captive site wild
147.3261 144.8698 148.2895

4.Outliers
5.Poorly behaved residuals

thanks for the answer I am open minded to any different kind of analysis.

Tobi



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