Hello R users,
My general understanding is that, in R , nominal categorical variables (with 2 or more levels) must be first converted into factors and THEN into to dummy variables (k-1 dummy variables for k levels - dummy encoding). Is that correct?
Once we accomplish categorical variable -> factor -> dummy variables transformation, we can then use the dummy variable as an independent or dependent variable in a statistical model (P.S. : when using the function lm() in R, the function lm() automatically does the dummy variable conversion but I am not sure that being true for other models).
What if we converted the categorical variable straight into dummy variables without the intermediate factor() step? Would that still work in R if we passed the dummy variables to a statistical model? I think so...Which means that we could really skip the conversion to factors..