[R] categorical varibles in coxph

[Thomas Lumley]

On Fri, 15 Oct 2004, Lisa Wang wrote:

> Hello,
>
> I wonder when I do coxph in R:
>
> coxph( Surv(start, stop, event) ~ x, data=test)
>
> If x is a categorical varible (1,2,3,4,5), should I creat four dummy
> varibles for it? if yes, how can I get the overall p value on x other
> than for each dummy variable?
>

No. Use
   coxph( Surv(start, stop, event) ~ factor(x), data=test)
or define x as a factor.

For an overal test use anova(): eg

> data(pbc)
> model<-coxph(Surv(time,status)~factor(edtrt)+bili, data=pbc)
> model
Call:
coxph(formula = Surv(time, status) ~ factor(edtrt) + bili, data = pbc)


                   coef exp(coef) se(coef)    z       p
factor(edtrt)0.5 0.629      1.88   0.2297 2.74 6.2e-03
factor(edtrt)1   1.664      5.28   0.2762 6.02 1.7e-09
bili             0.119      1.13   0.0129 9.29 0.0e+00

Likelihood ratio test=127  on 3 df, p=0  n= 418
> anova(model)
Analysis of Deviance Table
  Cox model: response is Surv(time, status)
Terms added sequentially (first to last)

                Df Deviance Resid. Df Resid. Dev
NULL                             418    1746.94
factor(edtrt)   2    62.13       416    1684.82
bili            1    65.11       415    1619.71
> summary(model)
Call:
coxph(formula = Surv(time, status) ~ factor(edtrt) + bili, data = pbc)

   n= 418

                   coef exp(coef) se(coef)    z       p
factor(edtrt)0.5 0.629      1.88   0.2297 2.74 6.2e-03
factor(edtrt)1   1.664      5.28   0.2762 6.02 1.7e-09
bili             0.119      1.13   0.0129 9.29 0.0e+00

                  exp(coef) exp(-coef) lower .95 upper .95
factor(edtrt)0.5      1.88      0.533      1.20      2.94
factor(edtrt)1        5.28      0.189      3.07      9.07
bili                  1.13      0.887      1.10      1.16

Rsquare= 0.262   (max possible= 0.985 )
Likelihood ratio test= 127  on 3 df,   p=0
Wald test            = 193  on 3 df,   p=0
Score (logrank) test = 281  on 3 df,   p=0