Given interval censored survival times, how do I perform an interval censored Cox PH model in R? An rseek search turns up the package intcox, which no longer exists in the R repository. I'm almost positive the coxph function in the survival package cannot handle interval censored survival data.
Also, I don't want to impute the data and then use the coxph function. This method underestimates the standard errors of the coefficients because you are ignoring the uncertainty of the interval censoring.
Best Answer
As stated above, you can use the survreg function. A note though: this is not strictly a Cox PH model, but rather location-scale models. Using the default log-transformation, this is the aft model. In the case of the exponential distribution, the proportional hazards and aft model are equivalent, so if distribution is set to exponential, this is a proportional hazards model with an exponential baseline. Likewise, if a baseline Weibull distribution aft model is used, the parameter estimates are just a linear transformation of those used in the proportional hazards model with Weibull baseline distribution. But in general, survreg does not fit a Cox PH model.
If a semi-parametric model is desired, as found implemented in intcox, a word of caution: there are several issues with the current version of intcox (algorithm typically prematurely terminates significantly far from the MLE, fails outright with uncensored observations, no standard errors automatically presented).
A new alternative that you could use is the package "icenReg".
Admission of bias: this is the author of icenReg.