[R-sig-eco] Standardising and transformation of explanatory/independent/predictor variables for multiple regression analysis

[Samantha Cox]

Dear R-sig-ecology,

I have spent some time trawling the internet, and seem to come across slight conflicting advice regarding the standardisation and transformation of variables prior to multiple regression analysis (e.g. LM, LME/GLS, GLM, GLMM, GAM, GAMM).  I searched the archives here and I don't think this is a repeat, but I apologise if it is.


1.       I understand that standardisation (subtract mean and divide by standard deviation) is important within a Bayesian environment and when using programs such as Rjags.  However within frequentist packages (e.g. lme4, MASS etc) under what (if any) circumstances is it necessary?



2.       Are transformations (e.g. log, sqrt etc) necessary for non-normal (highly skewed) explanatory variables or where extreme/outliers are observed.  Some literature says this is necessary, other say it is not.  Is the current consensus that transformations are generally not required on predictor/explanatory variables?


Thank you

Sam
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