[amelia] Transformations

Dear Amelia group, Suppose my data set has a variable v that I want to include as a predictor variable in a regression model. Supoose that some transformation of v, for example, sqrt(v) or log(50 - v), looks more normally distributed than v does. However, to keep the interpretation of the model simpler, I want to include v itself as a predictor variable, not a transformation of v. What I had been doing previously was to use the "sqrts" or "logs" argument of amelia(), and then use v (not the transformed v) in the model. Or if a different transformation was required, I would create the transformed variable then impute (with v as an idvar) then back-transform, and use the back-transformed v in the model. Is this considered poor practice because I was using the transformed v for imputation but using v itself in the regression model? If it is, would I be better off simply imputing without using any transformation of v, assuming that v is the variable I want to include in the regression model? Thanks for any advice, and thanks to the Amelia team for all their work. Mark