I have a data set with seven inputs. Four of which are categorical. For my
midterm, my professor wants us to scale all the inputs. This means, I
pressume, that I have to use 'recode' or 'factor' to transform the
categorical data in numerical. For example, one input variable is
'race=(b,w,h,o)'. I just want to assign a numerical value to all
'b,w,h,o'. I thought 'recode' should do this, but it doesn't work. Here's
the code I'm using for recode:
recode(race, "b='1';w='2';h='3';o='4'")
this is the error I get:
Error in eval(expr, envir, enclos) : object "o" not found
It's not that there's no "o". If I change the order or combination of the
variables, it always can't find one of them.
I could also use 'factor', from what I hear. But, I looked at the help
section on this function and I ended up more confused.
How do I code it so these variables take on numerial values? I need to be
able to use:
race.centered = race - mean(race)
This scaling code doesn't really make sense if the values of 'race' are
non-numerical. I might end up dividing by 2 SD's as well. But, I don't
know if I need to. I'll have to do some more reading.
Thank you for your help!
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