richard.cot...@hsl.gov.uk writes:
> The best encoding depends upon which language you would like to manipulate
> the variable in. In R, genders are most naturally represented as factors.
> That means that in an external data source (like a spreadsheet of data),
> you should ideally have the gender recorded as human-understandable text
> ("male" and "female", or "M" and "F"). Once the data is read into R, by
> default R will convert the string to factors (keeping the human readable
> labels). This way you avoid having to remember that 1 means male (or
> whatever).
>
> If you were manipulating the data in a different language that didn't have
> factors, then it might be more appropriate to use an integer. Which
> integers you use doesn't matter, you need to have a look-up table to know
> what each number refers to, whatever you choose.
>
Yes, that's what I thought. However somebody told me that it is better
to use 1/2 rather than 0/1 for a 2 level factor such as gender, and I've
no idea why. I told them it didn't matter, but have since seen quite a
few examples where they use 1/2 (admittedly in SPSS).
--
aleblanc
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