Thanx Mate !! @PaigeMiller wrote: @pathakvishal wrote: I am using PROc Reg (Selection = stepwise ) linear regression for banking data which has credit customer information for which we need to predict the factor affecting the usageof credit card. In output of PRoc Reg . My model is giving of the final factors(dummyvariable factors) as dummy_card1 meaning( amex) dummy_card4 meaning(discover), (both are types of primary ) refer to screenshot for more clarity these card are primary credit cards My question is can we have a final model in which we can have 2 dummy variables from same categorical variables . Yes, of course you can. Also , can we reduce the number of variable even after the output of ( selection = stepwise ). ? Yes, you can do this too, but I wouldn't, because stepwise provides the result that if finds to be the best fit model. I would however recommend that stepwise isn't highly regarded by most statisticians these days, and perhaps something like PROC PLS might be a better alternative with multiple input variables that are correlated.
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