Description Usage Arguments Details Value References Examples
This function tests for quasi-independence between the survival and truncation times. The survival and truncation times must be quasi-independent to use coxDT and cdfDT.
1 | indeptestDT(y, l, r)
|
y |
vector of event times |
l |
vector of left truncation times |
r |
vector of right truncation times |
Testing for quasi-independence between the survival and truncation times using the conditional Kendall's tau introduced by Martin and Betensky (2005). More details are given in their paper.
tau |
Conditional Kendall's tau for survival time and left truncation time and survival time and right truncation time |
X2 |
Chi-squared test statistic to test null hypothesis that survival and truncation times are quasi-independent. Default degrees of freedom (DF) is 2. If left and right truncation times perfectly correlated, DF = 1 |
p |
p-value for null hypothesis that survival and truncation times are quasi-independent |
Martin and Betensky (2005). Testing Quasi-Independence of Failure and Truncation Times via Conditional Kendall's Tau. JASA. 100(470):484-492.
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