[R] interpreting coxph results
Thomas Hills
thills at indiana.edu
Mon Aug 21 16:05:26 CEST 2006
I am having trouble understanding results I'm getting back from coxph
doing a recurrent event analysis. I've included the model below and
the summary. In some cases, with minor variations, the Robust
variance and Wald tests are significant, but the individual
covariates may or may not be significant. My main question is: If
Wald and robust tests both take into account the clustering, then why
are they so different and how do I make sense of them. A second
question is: If Wald and Robust are both significant in the summary
tests, but all individual covariates are insignificant (these are
Wald, yes?), what do I make of that? I recognize the questions are
partly R related and partly statistical (if there is a better place
to post this please let me know).
Call:
coxph(formula = Surv(startt, stopt, rep(1, nrow(omfi))) ~ joof1 +
topslope1 * top1 + I(early.angle/late.angle) + spac.cov +
ave.angle + slopef.d + cluster(id) + strata(sequence), data =
thedofile))
n= 174
coef exp(coef) se(coef) robust se
z p
joof1 -0.2755 7.59e-01 0.1590 0.2998 -0.919
0.36
topslope1 30.9827 2.86e+13 23.2339 51.9948 0.596
0.55
top1 0.1165 1.12e+00 0.1901 0.3951 0.295
0.77
I(early.angle/late.angle) 0.0449 1.05e+00 0.1165 0.1296 0.347
0.73
spac.cov 0.9815 2.67e+00 3.4104 5.5871 0.176
0.86
ave.angle 0.0396 1.04e+00 0.0156 0.0266 1.488
0.14
slopef.d -0.3394 7.12e-01 0.4373 0.8891 -0.382
0.70
topslope1:top1 -5.5673 3.82e-03 2.8198 6.7696 -0.822
0.41
Rsquare= 0.18 (max possible= 0.898 )
Likelihood ratio test= 34.5 on 8 df, p=3.27e-05
Wald test = 23.5 on 8 df, p=0.00276
Score (logrank) test = 31.8 on 8 df, p=0.000103, Robust = 13.5
p=0.097
(Note: the likelihood ratio and score tests assume independence of
observations within a cluster, the Wald and robust score tests
do not).
Thanks for any help,
Thomas Hills
Indiana University
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