TimeVTree (version 0.3.1)

prune: Function to Prune Using the Score Statistic

Description

This function merges over-segmented intervals to create optimally pruned subtrees.

Usage

prune(fulltree)

Arguments

fulltree

output from output.coxphout

Value

prune returns a matrix with the following columns, where each row is an optimally pruned subtree:

K

subtrees number 1, 2, etc. Tree #1 is the full tree

N[1]

Number of terminal nodes

alpha

penalty parameter corresponding to the subtree

S[1]

-log(partial likelihood) of the subtree

pruneoff

Node that was removed from the previous larger subtree to obtain the current subtree

Details

prune uses the CART algorithm and -log (partial likelihood) as cost to find the optimally pruned subtrees.

References

Xu, R. and Adak, S. (2002), Survival Analysis with Time-Varying Regression Effects Using a Tree-Based Approach. Biometrics, 58: 305-315.

Examples

# NOT RUN {
##Call in alcohol data set
data('alcohol')
require(survival)

coxtree <- coxph.tree(alcohol[,'time'], alcohol[,'event'], 
                      x = alcohol[,'alc', drop = FALSE], D = 4)
nodetree <- output.coxphout(coxtree)

subtrees <- prune(nodetree)
# }