ksurvcurves: k-groups of multiple survival curves

In clustcurv: Determining Groups in Multiples Curves

Description

Function for grouping survival curves, given a number k, based on the k-means or k-medians algorithm.

Usage

ksurvcurves(
  time,
  status = NULL,
  x,
  k,
  kbin = 50,
  algorithm = "kmeans",
  seed = NULL
)

Arguments

time	Survival time.
status	Censoring indicator of the survival time of the process; 0 if the total time is censored and 1 otherwise.
x	Categorical variable indicating the population to which the observations belongs.
k	An integer specifying the number of groups of curves to be performed.
kbin	Size of the grid over which the survival functions are to be estimated.
algorithm	A character string specifying which clustering algorithm is used, i.e., k-means("kmeans") or k-medians ("kmedians").
seed	Seed to be used in the procedure.

Value

A list containing the following items:

measure	Value of the test statistics.
levels	Original levels of the variable x.
cluster	A vector of integers (from 1:k) indicating the cluster to which each curve is allocated.
centers	An object of class survfit containing the centroids (mean of the curves pertaining to the same group).
curves	An object of class survfit containing the survival curves for each population.

Author(s)

Nora M. Villanueva and Marta Sestelo.

Examples

library(clustcurv)
library(survival)
data(veteran)

# Survival: 2 groups k-means
s2 <- ksurvcurves(time = veteran$time, status = veteran$status,
x = veteran$celltype, k = 2, algorithm = "kmeans")

data.frame(level = s2$level, cluster = s2$cluster)


# Survival: 2 groups k-medians
s22 <- ksurvcurves(time = veteran$time, status = veteran$status,
x = veteran$celltype, k = 2, algorithm = "kmedians")

data.frame(level = s22$level, cluster = s22$cluster)

clustcurv documentation built on Jan. 14, 2021, 5:32 a.m.