Consider a mixed model generated using the lme function in R. How can I consider the Box-cox transformations of this model in R? I have seen similar questions being asked before but they did not give specific references to the R code which is to be used.
Secondly, it is reasonable to consider the same linear model but without the random effects, and then use the transformation from this analysis in the mixed model? What would be explanation behind being able to/ not being able to do this? I would argue that on average the random factors are zero (hence this approach may work), but I do not have a definite answer.
Also, box cox should be considered before or after running significance tests for the different parameters in the model?