ComparisonCR (version 1.0.4)

ABC.perm: The permutation test of area between the CIF curves for competing risk data

Description

Statistical inference of area between the CIF curves (ABC) test with a permutation procedure for competing risk data.

Usage

ABC.perm(time, status, group, t0=0, tau=NULL, nperm=1000, seed=12345, bias=FALSE)

Arguments

time

The followed up time for testing data.

status

The status indicator, should be coded as 0= censored, 1= event of interest, 2= all other competing events.

group

The group indicator for comparison, and the elements of this vector should take either 0 or 1. Normally, 0= control group, 1= treatment group.

t0

The start time point for testing, the default is set as t0=0 for overall test.

tau

The truncation time point for testing, which needs to be smaller than or equal to the minimum of the largest observed time in each of the two groups. When tau=NULL, the default value is used. See details in reference.

nperm

The times of permutation, with default nperm=1000.

seed

The seed number, with default seed=12345.

bias

If bias=TRUE, the results will print the mean difference for delta of simulated datasets and original data. The default is bias=FALSE

Value

t0

The start time point for testing.

tau

The truncation time point for testing.

delta

The alsolute difference of two cumulative incidence functions.

var(delta)

The variance for delta of simulated datasets.

bias

The mean difference for delta of simulated datasets and original data.

Pvalue

The P value of this test.

References

Lyu J, Chen J, Hou Y, Chen Z. Comparison of two treatments in the presence of competing risks. Pharmaceutical Statistics, 2020. DOI: 10.1002/pst.2028.

Examples

# NOT RUN {
#get dataset from package
data(crossdata)
#just for an example, we set resampling times at 10
#overall test
ABC.perm(crossdata$time, crossdata$status, crossdata$group, nperm=10)
#arbitary test for detecting difference after 2 years
ABC.perm(crossdata$time, crossdata$status, crossdata$group, t0=2, tau=NULL, nperm=10)
#arbitary test for detecting difference between 2 years and 4 years
ABC.perm(crossdata$time, crossdata$status, crossdata$group, t0=2, tau=4, nperm=10)
# }