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Re: st: alternative to SW in Stata


From   Ricardo Ovaldia <ovaldia@yahoo.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: alternative to SW in Stata
Date   Thu, 12 Jul 2012 12:54:33 -0700 (PDT)

Thank you for the siuggestion David. However, the idea is to identify those (risk factors) variables that are most highly associated with time to failure. By creating factors scores using factor analysis, I lose the ability to identify these important variables individually. 

Ricardo

Ricardo Ovaldia, MS
Statistician 
Oklahoma City, OK


--- On Thu, 7/12/12, David Greenberg <dg4@nyu.edu> wrote:

> From: David Greenberg <dg4@nyu.edu>
> Subject: Re: st: alternative to SW in Stata
> To: statalist@hsphsun2.harvard.edu, ovaldia@yahoo.com
> Date: Thursday, July 12, 2012, 2:41 PM
> If some of your predictors can be
> understood as multiple imperfect
> indicators of an underlying latent variable, you could
> create a scale
> by doing a factor analysis of your predictors, and using the
> factor
> scores in the Cox regression. David Greenberg, Sociology
> Department,
> NYU
> 
> On Thu, Jul 12, 2012 at 2:55 PM, Ricardo Ovaldia <ovaldia@yahoo.com>
> wrote:
> > Hello,
> >
> > We recently submitted a manuscript where we use -stcox-
> and the stepwise procedure to reduce the number of potential
> risk factors from 30 to 5. One reviewer commented that using
> stepwise was inappropriate but did not provide an
> alternative other than to say that we should retain all 30
> factors. Giving our sample size (n=1000 and 105 failures)
> retaining all the factors would result in an over-fitted
> model. I know that there are limitations to using stepwise,
> many already discussed on statalist, bt we felt that the
> results we obtained were reasonable based on the science and
> current literature. However, what would be an alternative to
> SW for –stcox-? Is there a command in Stata or can someone
> suggest an acceptable method to generate a more parsimonious
> model?
> >
> > Thank you in advance,
> > Ricardo
> >
> >
> > Ricardo Ovaldia, MS
> > Statistician
> > Oklahoma City, OK
> >
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