[R] Pairwise comparisons/contrasts from a coxph model?
pflugshaupt at geobot.umnw.ethz.ch
Tue Jun 20 16:07:47 CEST 2000
this is probably more a statistical question than an R-specific problem, but
I'll risk it.
I've fitted a Cox Proportional hazard model with one factor Treatment (seven
levels) as a predictor variable. The general Null hypothesis (all groups
show the same survival behaviour) is clearly rejected. Now, is there any
(statistically sensible) way of doing pairwise comparisons and/or contrasts
In the R online help as well as in the literature I've looked up (I'll look
up more), nothing of the sort is mentioned. Does this mean it's not a
reasonable thing to do, or that it's trivial? :-)
And, has somebody already done this in R or could give me a hint?
One way I considered was (for all pairs of levels) to exclude all but the
respective two levels from my data and run the model. In the end I would do
a Bonferroni correction on all the p values I receive. Seems to be on the
save side, maybe too much so. Anyway, there ought to be a more elegant way.
Thankful for any hint
Here's the output from my model
coxph(formula = Surv(Week, Cens) ~ Treatment, data = poll.survdata2)
coef exp(coef) se(coef) z p
TreatmentT1 0.342 1.408 0.256 1.337 0.18000
TreatmentT2 0.102 1.108 0.246 0.416 0.68000
TreatmentT3 0.205 1.227 0.247 0.829 0.41000
TreatmentT4 -0.303 0.739 0.256 -1.184 0.24000
TreatmentT5 -1.066 0.344 0.306 -3.485 0.00049
TreatmentT6 -0.733 0.480 0.281 -2.611 0.00900
Likelihood ratio test=30 on 6 df, p=3.89e-05 n= 210
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