Computes the conditional Kendall's tau and inference
cKendall(trun, obs, delta = NULL, method = "MB", weights = NULL, a = 0, trans = "linear", ...)
| trun | left truncation time satisfying |
|---|---|
| obs | observed failure time, must be the same length as |
| delta | an optional 0-1 vector of censoring indicator (0 = censored, 1 = event) for |
| method | a character string specifying the different version of conditional Kendall's tau to be computed. The following are permitted:
|
| weights | an optional vector of sampling weights used when |
| a | a numeric transformation parameter. The default value is 0, which applies no transformation.
This parameter must be greater than |
| trans | a character string specifying the transformation structure. The following are permitted:
|
| ... | for future methods. |
This function performs statistical test for quasi-independence between truncation time and failure time. The hypothesis test is based on the conditional Kendall's tau of Martin and Betensky (2005) and the two versions of the inverse probability weighted Kendall's tau of Austin and Betensky (2014).
The output contains the following components:
consistent point estimate of the conditional Kendall's tau.
asymptotic standard error of the conditional Kendall's tau estimator.
the value of the normal test statistic.
the (Wald) p-value of the test.
the transformation model (if applied).
the estimated transformation parameter.
Martin E. and Betensky R. A. (2005), Testing quasi-independence of failure and truncation times via conditional Kendall's tau, Journal of the American Statistical Association, 100 (470): 484-492.
Austin, M. D. and Betensky R. A. (2014), Eliminating bias due to censoring in Kendall's tau estimators for quasi-independence of truncation and failure, Computational Statistics & Data Analysis, 73: 16-26.
data(channing, package = "boot") chan <- subset(channing, sex == "Male" & entry < exit) attach(chan) cKendall(entry, exit, cens)#> #> Test for quasi-independence with conditional Kendall's tau #> #> Call: cKendall(trun = entry, obs = exit, delta = cens) #> #> Kendall's tau = 0.1967 , SE = 0.0958 , Z = 2.0529 , p-value = 0.0401 #>cKendall(entry, exit, cens, method = "IPW1")#> #> Test for quasi-independence with conditional Kendall's tau #> #> Call: cKendall(trun = entry, obs = exit, delta = cens, method = "IPW1") #> #> Kendall's tau = 0.1356 , SE = 0.0927 , Z = 1.4631 , p-value = 0.1434 #>cKendall(entry, exit, cens, method = "IPW2")#> #> Test for quasi-independence with conditional Kendall's tau #> #> Call: cKendall(trun = entry, obs = exit, delta = cens, method = "IPW2") #> #> Kendall's tau = 0.425 , SE = 0.174 , Z = 2.4423 , p-value = 0.0146 #>detach(chan)