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From |
"Austin Nichols" <austinnichols@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: selection correction in survival models |

Date |
Thu, 11 Sep 2008 09:59:58 -0400 |

Murali Kuchibhotla <muralik@iastate.edu>: A better question might be: Is there a way to correct for this in the real world? Probably not, in most senses. Think of it as a logit/probit regressing "survival" on the k variables in X and a training dummy T and the k interactions T*X, so you have at least k+1 endogenous variables measuring the effects of training. You could switch to an -ivprobit- model if you had a large number of instruments, but that seems unlikely (plus, I think you would want an -ivcloglog- command which does not exist). One way forward is to reweight the samples so they look identical on observables, using propensity scores, as described in http://www.stata-journal.com/article.html?article=st0136 and elsewhere (the sample will look identical in the sense that a -hotelling- test would fail to reject the null that the mean of X is the same in the training group and the non-training group--the distributions may differ in other ways). But this corrects only for selection on observables, not unobservable differences--for the latter, you need training to be randomly assigned, for a start. Or you need a very convincing natural experiment. On Wed, Sep 10, 2008 at 11:22 PM, Murali Kuchibhotla <muralik@iastate.edu> wrote: > > Hello, > I am interested in estimating separate Cox regression models for 2 > groups of individuals- trainees and non-trainees. The problem is that the > training decision is endogenously determined, so that the differences > between the 2 sets of parameter estimates may well be driven by the > differences in the unobservable characteristics between the 2 groups of > respondents. Is there a way to correct for this in Stata? > > Murali Kuchibhotla * * 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/

**References**:**st: selection correction in survival models***From:*"Murali Kuchibhotla" <muralik@iastate.edu>

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