These are very general questions, so you get a very general advise:
1) In general I would be hesitant to turn a continuous variable into a
categorical variable.
2) Look at your residuals.
-- Maarten
--- Andrea Bennett <[email protected]> wrote:
> Dear all,
>
> Right now I am wondering what is the better way to deal with
> categorical information.
>
> 1.
> What is about the best way to implement income groups into a
> regression? E.g. as income has (usually) no upper limits, I tend to
> generate an interaction term (dummy==1) if the individual is in the
> highest income category (0 if else). Further, am I right in the
> assumption that building categories is usually not sensible when the
>
> number of observations is high? One issue I face is that very young
> adults and very old adults are under-represented in the dataset
> (meaning, not that many unique observations for these groups, sample
>
> itself is good). Is there a rule of thumb what would be better,
> building categories for all age-classes (increasing observations in
> young/old group) or do not build classes at all (having more detailed
>
> info)? It's clearly a trade-off but maybe there's some advice. I tend
>
> not to use categories here, also because age-squared might be
> important to have at hand, later.
>
> 2.
> The "xi" command can help to make life less messy (in large data
> sets,
> I think). But it seems to kill all my value labels in these
> categorical groups! I could not find any option to tell "xi" to use
> the already defined value labels. Is there a workaround at hand so
> that the regression table will instead use the values defined (e.g.
> for sex; 0==male, 1==female) as new variable names?
>
> Many thanks for all your inputs,
>
> Andrea
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>
-----------------------------------------
Maarten L. Buis
Department of Social Research Methodology
Vrije Universiteit Amsterdam
Boelelaan 1081
1081 HV Amsterdam
The Netherlands
visiting address:
Buitenveldertselaan 3 (Metropolitan), room Z434
+31 20 5986715
http://home.fsw.vu.nl/m.buis/
-----------------------------------------
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