[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]

From |
moleps islon <moleps2@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Survival analysis |

Date |
Mon, 31 Aug 2009 01:29:23 +0200 |

Nice trick. However what I´m looking for is a way to find the exact time analytically from where the curves are parallel. I believe the PH assumption is fulfilled before and after this point. M On Mon, Aug 31, 2009 at 12:44 AM, Maarten buis<maartenbuis@yahoo.co.uk> wrote: > --- On Sun, 30/8/09, moleps islon wrote: >> I´m investigating the effect of a dichotomous variable on >> survival. Looking at the graphs they are parallell after >> the first 48 hrs, but there is a difference within the >> first 48 hrs. Is it reasonable to present the cox >> regression analysis with all the patients and then >> discard the patients dead within 48 hrs and redo the >> analysis-(this gives a significant effect in the first >> analysis and non-significant in the latter as suspected >> from the graphs)? Or is there a more analytical way to find >> the exact time from which the two groups no longer differ? > > I would do something like in the example below. In this example > the effect of age is allowed to change linearly over time for > the first 10 months, and afterwards the proportional hazard > assumption is maintained. The trick is that -(_t < 10)- is a > logical statement, so it evaluates to 1 if it is true, and 0 > if it is false (for more on this, see: > http://www.stata.com/support/faqs/data/trueorfalse.html ). So > for the first 10 months age is interacted with 1*_t, while for > the remaining months age is interacted with 0*_t. The effect > age in "rh equation" is the effect of age after 10 months, i.e. > after 10 months the hazard of death increased 12% for every > year of age. The effect of age in t equation tells you that in > the first 10 months the effect of age increased every month by > .0033%. > > *--------- begin example ----------- > sysuse cancer, clear > stset studytime, failure(died) > xi: stcox i.drug age, /// > tvc(age) texp((_t < 10)*_t) > *---------- end example ------------- > ( For more on how to use examples I sent to statalist see: > http://www.maartenbuis.nl/stata/exampleFAQ.html ) > > 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/ > * * 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**:**Re: st: Survival analysis***From:*Maarten buis <maartenbuis@yahoo.co.uk>

**References**:**st: Survival analysis***From:*moleps islon <moleps2@gmail.com>

**Re: st: Survival analysis***From:*Maarten buis <maartenbuis@yahoo.co.uk>

- Prev by Date:
**Re: st: Equivalent STATA cmmand for "ADD FILES" in SPSS** - Next by Date:
**st: Getting entity specific slopes in one command** - Previous by thread:
**Re: st: Survival analysis** - Next by thread:
**Re: st: Survival analysis** - Index(es):

© Copyright 1996–2016 StataCorp LP | Terms of use | Privacy | Contact us | What's new | Site index |