selectCox: Backward variable selection in the Cox regression model
Description
This is a wrapper function which first selects variables in the Cox
regression model using fastbw from the rms package and
then returns a fitted Cox regression model with the selected variables.
Usage
selectCox(formula,data,rule="aic")
Arguments
formula
A formula object with a Surv object on the
left-hand side and all the variables on the right-hand side.
data
Name of an data frame containing all needed variables.
rule
The method for selecting variables. See
fastbw for details.
Details
This function first calls cph then fastbw and finally
cph again.
References
Ulla B. Mogensen, Hemant Ishwaran, Thomas A. Gerds (2012). Evaluating Random Forests
for Survival Analysis Using Prediction Error Curves. Journal of Statistical Software,
50(11), 1-23. URL http://www.jstatsoft.org/v50/i11/.