konp_test {KONPsurv}R Documentation

KONP tests are K-sample Omnibus Non-Proportional hazards tests for right-censored data.

Description

KONP tests are K-sample Omnibus Non-Proportional hazards tests for right-censored data.

Usage

konp_test(time, status, group, n_perm, n_impu = 1)

Arguments

time

A vector of the observed follow-up times.

status

A vector of event indicators, 0=right censored, 1= event at time.

group

A vector denoting the group labels, must contain at least two different values.

n_perm

The number of permutations.

n_impu

The number of imputations, for each imputation n_perm permutations will be executed.

Details

The KONP tests are powerful non-parametric tests for comparing K (>=2) hazard functions based on right-censored data. These tests are consistent against any differences between the hazard functions of the groups. The KONP tests are often more powerful than other existing tests, especially under non-proportional hazard functions.

Value

Three test statistics and their respective p-values are returned:

pv_chisq - returns the p-value based on the KONP test chi-square statistic.
pv_lr - returns the p-value based on the KONP test likelihood ratio statistic.
pv_cauchy - returns the p-value based on the KONP-based Cauchy-combination test statistic.
chisq_test_stat - returns the KONP test chi-squared test statistic.
lr_test_stat - returns the KONP test likelihood-ratio test statistic.
cauchy_test_stat - returns the KONP-based Cauchy-combination test statistic.

Examples

## Generate some data to preform the test
set.seed(1)
n <- 50
time <- rexp(n)
status <- sample(c(0,1),n,TRUE)
group <- c(rep(1,25),rep(2,25))

konp_test(time,status,group,n_perm=10^3)


[Package KONPsurv version 1.0.1 Index]