I am new with statistics and especially stepwise regression with categorical variables. I have 4 categorical variables, each with a different levels (5 levels, 12 levels, 7 levels, and 78 levels). I used the following to do stepwise in R
null.lm <- lm(log(bid)~1, data=data) full.lm <- lm(log(y)~log(x) + program + month+ region + code , data=data) step(null.lm, scope=list(lowr=null.lm, upper=full.lm), directiom="both")
The resulting stepwise model containing the following output:
codeStructure month02 month03 month04 month05 0.150322 0.103917 -0.065815 0.007522 -0.004914
then I used
predict(step(null.lm, scope=list(lowr=null.lm, upper=full.lm), directiom="both"))
to find the predicted values.
My question is: Was I supposed to create a dummy variable for each level?I mean for the month categorical variable: create 12 columns (1,0) and then use this in the stepwise? I use stepwise because when fitting the linear model, not all p-values were significant, so I though of doing variable selection, but I am not sure if what i did is correct.
If I had to use the step outcome: if the observation belongs to month02, then I multiply its coefficient by 1, otherwise by 0?