It seems to me that R returns the unpenalized log-likelihood for the ratio
likelihood test when ridge regression Cox proportional model is implemented. Is
this as expected?
In the example below, if I am not mistaken, fit$loglik[2] is unpenalized
log-likelihood for the final estimates of coefficients. I would expect to get
the penalized log-likelihood. I would like to check if this is as expected. If
not, I am prepared to give more details. Cheers,DK.
For example, if we have a model
> fit <- coxph(Surv(futime, fustat) ~ ridge(rx, age, ecog.ps,
> theta=1),data=ovarian)
> fit$loglik
[1] -34.98494 -27.17558
> fit
Call:
coxph(formula = Surv(futime, fustat) ~ ridge(rx, age, ecog.ps,
theta = 1), data = ovarian)
coef se(coef) se2 Chisq DF p
ridge(rx) -0.780 0.5862 0.5589 1.77 1 0.1800
ridge(age) 0.123 0.0387 0.0356 10.15 1 0.0014
ridge(ecog.ps) 0.104 0.5729 0.5478 0.03 1 0.8600
Iterations: 1 outer, 4 Newton-Raphson
Degrees of freedom for terms= 2.7
Likelihood ratio test=15.6 on 2.67 df, p=0.000941 n= 26
> fit$loglik[2]
[1] -27.17558
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