After execution of an experiment (CCD), I realized that it makes sense to log-transform one of the factors (I do it in the fit model dialog), which eventually gives a decent fit. However, the linear and square term have a high correlation then (VIF = 56). When manually transforming this factor, the VIF is low (VIF < 2). Can someone explain to me how this can happen and how I can avoid it?
I tried with my data but didn't see this behavior. Could you share the data and the models you ran?
Attached now the file - should be self explanatory, just run the two models and check the VIFs. I am actually wondering, if it is related to the coding somehow. If using the "transform" option, I cannot code.
Yes, getting high VIFs is a result of the square term, Log(B)*log(B), not centered. (Center Polynomials is the default option when higher order terms are specified as model effects in Fit Model see Model Specification Options)
Somehow JMP won't automatically center the crossed terms on the transformed variables created temporarily within the Fit Model window.
The work around is just like what you already did: saving the transformed columns to your data table before you specify your models. Are you using this feature Transform Columns? It lets you quickly create new columns (e.g.,log) in Fit Model launch window (in the column list pane) and then use Add to Data Table option to save them--done with two right mouse clicks.
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