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From |
Maarten Buis <maartenlbuis@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: Subject: Re: st: Survival function of regression Cox model postestimation |

Date |
Tue, 12 Jul 2011 19:00:45 +0200 |

--- On Fri, Jul 8, 2011 at 8:13 PM, Mario Petretta wrote: >>> I know that the baseline survival function of the Cox model without >>> covariates is the same as the Kaplan Meier survival function. >>> However, it is unclear for me why the survival function of a Cox model with >>> covariates obtained at the mean values of the covariates is different from >>> baseline survival function of the Cox model without covariates. --- Maarten Buis answered >> Because the relationship between the covariates and the survivor >> function is a non-linear one. Remember that applying a non-linear >> transformation to a variable x and than compute the mean is not the >> same as computing the mean of variable x and than apply that >> non-linear transformation. --- On Tue, Jul 12, 2011 at 6:40 PM, Mario Petretta wrote me privately: > Anyway, there is a rule for applying a non-linear transformation to a > continuous covariate in order to obtain a survival function of a Cox model > with that covariate obtained at its mean value not different from > baseline survival function of the Cox model without covariates? It is better to respond to the Statalist and not privately because if you find my answer unclear, chances are that other people following this thread may also find it unclear. No, Cox regression has a baseline hazard function not a baseline survival function, and the baseline hazard function is the hazards at different points in time when all explanatory/independent/x-variables are 0 not fixed at the mean. Hope this helps, Maarten -------------------------- Maarten L. Buis Institut fuer Soziologie Universitaet Tuebingen Wilhelmstrasse 36 72074 Tuebingen Germany http://www.maartenbuis.nl -------------------------- * * 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/

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