Calculating AICc using conditional logistic regression

I have a case-control study that I'm analysing using the conditional
logistic regression function clogit from the survival package.

I would like to calculate the AICc of the models I fit using clogit.

I have a variety of scripts that can calculate AICc for models with a
logLik method, but clogit does not appear to use this method.

Is there a way I can calculate AICc from clogit in R?

Review

 	?logLik
 	?coxph.object

and then roll your own logLik.coxph.

Here is one version:

logLik.coxph <-
     function(object,...) {
         y <-  -1 * (object$loglik[1] - object$loglik[2])
         class(y) <- "logLik"
         attr(y,'df')<- sum(!is.na(object$coef))
         y
}

Try it like this:

fit <- clogit(case ~ spontaneous + induced + strata(stratum), data = 

infert)

logLik(fit)

'log Lik.' 26.57712 (df=2)

[...]

Charles C. Berry                        (858) 534-2098
                                          Dept of Family/Preventive Medicine
E mailto:cberry at tajo.ucsd.edu	         UC San Diego
http://biostat.ucsd.edu/~cberry/         La Jolla, San Diego 92093-0717