[R] variable transformation for lm
JRadinger at gmx.at
Thu Nov 3 16:55:08 CET 2011
I am doing a simple regression using lm(Y~X).
As my response and my predictor seemed to be skewed
and I can't meet the model assumptions. Therefore
I need to transform my variables.
I wanted to ask what is the preferred way to find out
if predictor and/or response needs to be transformed
and if yes how (log-transform?).
I found a procedure in "A modern approach to Regressoin
in R" (Sheather, 2009): There they suggest an approach
with the function bctrans from alr3...but it seems that it
is deprecated. So what is the best way (box-cox test) find the best
transformation for predictor and response simultaneously?
AFAIK boxcox from MASS is used only used for transformation
of the predictor?
Thank you very much
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