ABC.perm {ComparisonCR} | R Documentation |
Statistical inference of area between the CIF curves (ABC) test with a permutation procedure for competing risk data.
ABC.perm(time, status, group, t0=0, tau=NULL, nperm=1000, seed=12345, bias=FALSE)
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 |
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. |
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.
#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)