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From |
"Carlo Lazzaro" <carlo.lazzaro@tin.it> |

To |
<statalist@hsphsun2.harvard.edu> |

Subject |
st: R: Proportional hazards assumption in Cox model |

Date |
Wed, 25 Feb 2009 09:14:05 +0100 |

Dear Mingfeng, the usual test for checking the fulfilment of Cox proportional hazard assumption requirements is Schoenfeld residuals [in Stata 9.2/SE - schoenfeld(newvars)-]. Unfortunately, Cox proportional hazard assumption may not hold. An example about this lack of holding of Cox proportional hazard assumption (more frequent than usually reported I scientific articles, I suspect) can be found in Jes S Lindholt, Svend Juul, Helge Fasting and Eskild W Henneberg. Screening for abdominal aortic aneurysms: single centre randomised controlled trial. BMJ 2005;330;750-; originally published online 9 Mar 2005; doi:10.1136/bmj.38369.620162.82. The authors wrote "We used Cox proportional hazards regression to compare specific mortality due to abdominal aortic aneurysm and overall mortality. As the proportional hazards assumption was not fulfilled, we decided to carry out separate analyses for the periods before and after 1.5 years after randomisation". Hence, the moved to Kaplan-Meier estimates of mortality (a non parametric method that makes no assumptions about the underlying risk function). As an aside, Svend Juul is an epidemiologist and also a relevant contributor to Stata List. For further details on Survival analysis, I will recommend you to take a thorough look at: Cleves MA, Gould WG, Gutierrez R. An Introduction To Survival Analysis Using Stata. Revised edition. College Station: StataPress, 2006; [ST] Stata manual. Survival analysis and epidemiological table. Release 9. Kind Regards, Carlo -----Messaggio originale----- Da: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] Per conto di Mingfeng Lin Inviato: mercoledì 25 febbraio 2009 6.09 A: statalist@hsphsun2.harvard.edu Oggetto: st: Proportional hazards assumption in Cox model 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/ * * 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: Proportional hazards assumption in Cox model***From:*Mingfeng Lin <mingfeng.lin@gmail.com>

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