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Re: st: Cluster/PCA for predicting a binary outcome?


From   "K Jensen" <k.x.jensen@googlemail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Cluster/PCA for predicting a binary outcome?
Date   Wed, 18 Jul 2007 13:09:16 +0100

Thanks, Paul! This is part way towards what I was hoping to do.
I have a set of variables that more-or-less form groups that tend to
be correlated with each other, but not with the other variables.
I would like to produce more than one linear function a la "discrim"
for each of the groups. Or that would have one linear function that
has high weights on one group, another on the second and so on.
BTW, I am making the groups sound a lot more defined than they are; it
is more of a tendency than anything absolute.
Thankyou again
Karin

On 18/07/07, E. Paul Wileyto <epw@mail.med.upenn.edu> wrote:
You're looking for discriminant analysis (look up Stata help on
discrim)...  It's like PCA, but you can think of it as selecting the
loadings to maximize the F-value if you did a 1-way ANOVA by your class
variable.

But, for a binary outcome, many simply use logistic regression.

P

K Jensen wrote:
> Hi
> I am trying to predict a binary outcome from a set of correlated
> variables.  Rather than using logisitic regression to include the
> variables one-by-one in the model, I was wondering if there was a way
> in Stata of generating sets or functions of the variables?  Maybe
> something similar to PCA, except that you would be trying to explain
> the variation in the binary outcome rather than the whole dataset.
> I hope that this makes some sort of sense!
> Thankyou
> Karin
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--
E. Paul Wileyto, Ph.D.
Assistant Professor of Biostatistics
Tobacco Use Research Center
School of Medicine, U. of Pennsylvania
3535 Market Street, Suite 4100
Philadelphia, PA  19104-3309

215-746-7147
Fax: 215-746-7140
epw@mail.med.upenn.edu
http://mail.med.upenn.edu/~epw/

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