What inspired this wish list request?
StepWise Fit incorporates statistically invalid correlations into the model fit when there are a large number of parameters which are fit. JMP Stepwise criteria is only looking at Sum of Squares along with the F Ratio to produce what stays in the model. Then only when you Make and Run the final Stepwise Model do you get the Fit Group Effect Summary that gives you the option to get FDR Logworth and FDR PValues. An FDR alpha should be the default input for StepWise rather than the current inputs.
We had to research why JMP is failing to select the correct criteria for incorporating parameters into the fit.
Project Euclid (https://projecteuclid.orgtalking) talks about incorporating FDR in Stepwise and we implemented into Python since JMP could not perform this properly.
What is the improvement you would like to see?
Why is this idea important?