3.10 Bonus track 2: Machine Learning for estimating the Cox PH model

The rpart package builds R’s basic tree models of survival data. For an overview you can consult the section 8.4 of the rpart vignette.

Additionally, the new package ranger (Wright and Ziegler 2017) is a fast implementation of the Random Forests algorithm for building ensembles of classification and regression trees, working also with survival data. Since ranger() uses standard `Surv survival objects, it’s an ideal tool for getting acquainted with survival analysis in this machine-learning age.

Under construction…


Wright, Marvin N., and Andreas Ziegler. 2017. “ranger: A Fast Implementation of Random Forests for High Dimensional Data in C++ and R.” Journal of Statistical Software 77 (1): 1–17. doi:10.18637/jss.v077.i01.