Hello, 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 Johannes -- ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
