<>
The bootstrap is a stochastic process, i.e. -set seed- to get consistent results. For instance, note how -stepwise- throws out -ui- every now and then in the following code, whereas the analytic standard error helps -ui- stay in the model.
*****
webuse lbw2,clear
forv i=1/10{
stepwise, pr(.10): logit low age lwt race2 race3 smoke ptl ht ui, vce(bootstrap)
}
*with analytic VCE
stepwise, pr(.10): logit low age lwt race2 race3 smoke ptl ht ui
*****
HTH
Martin
-------- Original-Nachricht --------
> Datum: Sat, 21 Mar 2009 22:51:28 +0100
> Von: aegl <[email protected]>
> An: [email protected]
> Betreff: st: variable selection and bootstrap
> Hello,
>
> I need to run a logistic regression including several X variables . I
> therefore plan to use backwards selection to select the best predictors
> and I have read that it is possible to combine this approach with
> boostrap.
> I have tried using the following syntax :
>
> stepwise, pr(.10): logistic Y X1 X2 X3 X4 X5 X6 X7, vce(bootstrap)
>
> This gives a result that is different from using an alternative
> approach: first running the backwards selection on the original sample,
> and then using the bootstrap to compute the CIs.
>
> Does anybody know what I am doing by using this syntax ? Is there
> another way to run backwards selection procedures with bootstrap ?
>
> Thank you very much for any input.
>
> Joel Rebloch'
> Data analyst
> Grenoble, France
>
>
>
>
>
> *
> * For searches and help try:
> * http://www.stata.com/help.cgi?search
> * http://www.stata.com/support/statalist/faq
> * http://www.ats.ucla.edu/stat/stata/
--
Martin Weiss
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*
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