ABC.ts {ComparisonCR} | R Documentation |
Statistical inference of two-stage test. Stage I is the Li's test, and stage II is area between the CIF curves(ABC) test.
ABC.ts(time, status, group, nboot=1000, alpha=0.05, seed=12345)
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. |
nboot |
The times of bootstrap resamplings, with default as nboot=1000. |
alpha |
The overall significance level, with default as alpha=0.05. |
seed |
The seed number, with default seed=12345. |
method |
Three test results are involved, the Li's test, ABC test, and the two-stage test. |
statistic |
The statistic of the Li's test, ABC test, and the two-stage test. |
Pvalue |
The P value of the Li's test, ABC test, and the two-stage test. |
[1] Li JN, Rademacher JL, Zhang MJ. Weighted comparison of two cumulative incidence functions with R-CIFsmry package. Computer Methods and Programs in Biomedicine, 2014, 116(3): 205-214.
[2] 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 #two-stage test ABC.ts(crossdata$time, crossdata$status, crossdata$group, alpha=0.05, nboot=10)