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From |
Mingfeng Lin <mingfeng.lin@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
st: Proportional hazards assumption in Cox model |

Date |
Wed, 25 Feb 2009 00:09:11 -0500 |

Greetings! I have a quick question about Cox models: I understand that we need to test for the assumption of proportional hazards for all covariates, and if any one fails the test, we should be concerned about the statistical inference on that variable; plus we should consider things such as time varying effects, stratification, and so on. But what if none of these solves the problem? In particular, is it appropriate to say that if one set of variables passes the test, we can still be confident about the estimates of their coefficients - despite the failure of other variables and global tests? In other words, while we know that Cox models tend to be quite robust, how much latitude do we have in terms of the proportional hazards assumption? How robust is this model, just to be specific? I'm still learning event history analysis, and the papers that I have came across so far (empirical papers in social sciences) do not seem to actually test that assumption (or maybe they forgot to report the results), so I am just curious. Thank you very much for any suggestions you can provide. If you could refer me to specific papers on this, it would be really helpful. Mingfeng * * 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/

**Follow-Ups**:**st: R: Proportional hazards assumption in Cox model***From:*"Carlo Lazzaro" <carlo.lazzaro@tin.it>

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