Hello,
I am performing cross-validation on a number of survival models fitted with the
coxph function and would like to use the likelihood ratio test on the left-out
cases as the criteria for comparison of PCA, SPCA, ridge, lasso, etc. Is there
an easy way to do this? I think predict.coxph might be the answer but stumped
on the implementation.
For example, if I had
fit <- coxph(Surv(time, status) ~ age + ph.ecog + strata(inst),
lung[1:200,])
> fit
Call:
coxph(formula = Surv(time, status) ~ age + ph.ecog + strata(inst),
data = lung[1:200, ])
coef exp(coef) se(coef) z p
age 0.0125 1.01 0.0106 1.18 0.24000
ph.ecog 0.5371 1.71 0.1423 3.78 0.00016
Likelihood ratio test=19.7 on 2 df, p=5.17e-05 n= 198, number of events=
156
(2 observations deleted due to missingness)
How to test likelihood of this model on lung[201:228,] ?
Thanks for any advice,
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