I am a newbie in survival analysis and I would like to pose some simple questions, after reading numerous posts regarding how to perform survival analysis in R.
So, what I would like to know is:
Can survreg function of survival package handle combination of time – varying and fixed time independent variables?
Which are the mathematical formulations behind the following R commands:
Model 1: survreg(Time,Event) ~ Independent, dist = "w") and Model 2: survreg(log(Time),Event) ~ Independent, dist = "extreme")
Which of the above models can be considered as an AFT model?
In case anybody has tried fitting both models using a panel – like dataset, can easily understand that the coefficients are identical, though,
Model 2 tends to perform larger Mc Fadden's R – squared value. Why is this happening?
Best Answer
In response to this part of the question:
the answer is no. However, both the
flexsurvreg
from the flexsurv package and theaftreg
function from the eha can do this, and the syntax is very similar to that of thesurvival::surv
function.The discussion on this question may be useful.