
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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