The Annals of Statistics

Rank Tests for Independence for Bivariate Censored Data

Dorota M. Dabrowska

Abstract

The paper discusses statistics that can be used to test whether two failure times, say $X_1$ and $X_2$, are independent. The two variables are subject to right censoring so that what is observed is $Y_i = \min(X_i, Z_i)$ and $\delta_i = I(X_i = Y_i)$, where $(Z_1, Z_2)$ are censoring times independent of $(X_1, X_2)$. Statistics that generalize the Spearman rank correlation and the log-rank correlation are considered, as well as general linear rank statistics. The Chernoff-Savage approach is adopted to show that suitably standardized versions of these statistics are asymptotically normal under both fixed and converging alternatives.

Article information

Source
Ann. Statist., Volume 14, Number 1 (1986), 250-264.

Dates
First available in Project Euclid: 12 April 2007

https://projecteuclid.org/euclid.aos/1176349853

Digital Object Identifier
doi:10.1214/aos/1176349853

Mathematical Reviews number (MathSciNet)
MR829566

Zentralblatt MATH identifier
0597.62035

JSTOR