Quite how to get useful results from smoothing a binary response is not
clear to me.
If the data were proportions on (0,1) or even [0,1] I would suggest
some kind of transformation approach. -lowess, logit- is presumably
intended to help.
Otherwise consider something like an angular or folded root
transformation, applying -lowess- and then transforming back.
But for binary data any transformation just maps two distinct values to
two other distinct values and so cannot help, so far as I can see.
In the case of unemployment data, presumably you are dealing with
individuals? If they are aggregate data for lots of individuals I would
collapse by age to get proportion of unemployed, and then smooth if
necessary. It sounds as if you want something quite different, however.
Also, as you regard -age- as categorical I probably don't understand
what you are trying to do.
Nick
[email protected]
Sergiy Radyakin
I am plotting a smoothed graph (-lowess-) of a binary variable (e.g.
unemployed) by categorical (e.g. age). However the smoothed values are
not necessarily in the [0;1] range, where unemployment must be by
definition. I can save the smoothed values into a new variable with
the option -generate(newvar)- and then truncate the negatives and
values larger than one, but I believe smoothing must look differently
if I could tell -lowess- to look for such a constrained value in the
first place. As it follows from the description of -lowess- it doesn't
have such a feature. Is there any user-written command or simple
algorithm for this purpose?
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