--- [email protected] wrote:
> How certain can I be that lnskew0 and bcskew0 have normalized the
> distribution for the variable have transformed with them (a percent)?
> After using these transformations, the histograms are still skewed.
> What could be the problem? Is it possible that they don't work in all
> instances?
you can find the skewness by typing -sum variable name, detail-.
There are distributions for which it won't work too well, for instance
if your distribution has a spike (one number that is very very common).
If your variable is a percentage than obvious candidates for spikes are
zero and a 100%.
What these commands try to do is to find a transformation that brings a
statistic called skewness, one number, as close to zero as possible.
This statistic is defined in reference manual entry for -summarize-.
Having that statistic close to zero is a necessary but not sufficient
condition for a variable to be normal(ized).
Furthermore, if variable is the dependent variable in a model than you
do not want that variable to be normal, but the residuals. So looking
at these type of statistics is not a good idea, you should be looking
at the residuals of your model. Moreover, you say that it is a
percentage. In that case you don't want to normalize (use -regress-) at
all, since there are better ways: -betafit- and -glm, family(binomial)
robust-. These are described in:
http://home.fsw.vu.nl/m.buis/software/betafit.html
Hope this helps,
Maarten
-----------------------------------------
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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