Hi all,

I have probably a basic question, but I can't seem to find the answer in
the literature or in the R-archives. 

I would like to do a robust ANCOVA (using either rlm or lmRob of the
MASS and robust packages) - my response variable deviates slightly from
normal and I have some "outliers". The data consist of 2 factor
variables and 3-5 covariates (fdepending on the model). However, the
variance between my groups is not equal and I am not sure if it is
therefore appropriate to use a robust statistical method or if a
non-parametric analysis (i.e. ranked regression) might be better. If I
can still use a robust statistical method, which estimator is best to
use to deal with unequal variance? And if it is better to use a
non-parametric analysis, could anyone put me in the direction of the
right non-parametric method to use (the relationship between my response
variable and the covariates is linear)?

Any help on this would be greatly appreciated!

Many thanks,
Geertje

~~~~
Geertje van der Heijden
PhD student
Tropical Ecology
School of Geography
University of Leeds
Leeds LS2 9JT

Tel: (+44)(0)113 3433345 
Email: g.m.f.vanderheijden04@leeds.ac.uk



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