[R] improvement of Ancova analysis

[Tobias Erik Reiners]

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