[R] Problem of COX model with time dependent covariate
dwinsemius at comcast.net
Mon Dec 26 13:49:33 CET 2011
On Dec 26, 2011, at 3:02 AM, JiangGZ wrote:
> Hi all,
> I am trying to detect association between a covariate and a disease
> outcome using R. This covariate shows time-varying effect, I add a
> time-covariate interaction item to build Cox model as follows:
> COX <- coxph(as.formula("Surv(TIME,outcome)~eGFR_BASE
> coef exp(coef) e(coef) z p
> eGFR_BASE 6.40 603.5133 0.3702 17.3 0
> eGFR_BASE:TIME -3.41 0.0329 0.0772 -44.2 0
> But the result seems very different from that got by SPSS:
> B SE Wald df Sig. Exp(B)
> eGFR_BASE -13.603 .548 616.007 1 .000 .000
> T_COV_*eGFR_BASE .860 .115 55.859 1 .000 2.362
> so my questions are :
> 1, Is it correct to deal with time dependent covariate in Cox
> regression using R? if not, how to do it ?
The usual way to represent time dependent covariates is to set up
records with start and stop time and use the Surv(time, time2, event)
usage. This is clearly described in the help page and there is
vignette describing time-dependent covariate methods in the package
> 2, How T_COV_ was calculated in SPSS, and is it the same with the
> survival time?
How could we possibly know how _you_ calculated T_COV? (And this is
very definitely the wrong mailing list for that question.)
The description in the IBM/SPSS documentation says using the time
variable on the RHS is used for testing non-proportionality of hazards
rather than for investigating the association of a covariate with an
The SPSS documentation appears designed to lead the naive user into an
incorrect model formulation, since the only example of use with its
dialog box shows the user setting up the test for non-proportionality.
Given that you proposed using a time variable on the RHS in an R
formula, I am guessing you also do not know how to properly use SPSS
for the purposes you intend.
> Many thanks.
> [[alternative HTML version deleted]]
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David Winsemius, MD
West Hartford, CT
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