Testing quasi-independence of failure and truncation times via conditional Kendall's tau.(failure time)(left-truncation time)(right-truncation time)

Journal of the American Statistical Association, June, 2005 by Betensky, Rebecca A.; Martin, Emily C.

Truncated survival data arise when the failure time is observed only if it falls within a subject-specific truncating set. Most analysis methods rely on the key assumption of quasi-independence, that is, factorization of the joint density of failure and truncation times into a product proportional to the individual densities in the observable region. Unlike independence of failure time and censoring time, quasi-independence can be tested. Tests of quasi-independence are available for one-sided truncation and for truncation that depends on a measured covariate, but not for more complex truncation schemes. Here tests of quasi-independence based on a multivariate conditional Kendall's tau are proposed for doubly truncated data, bivariate left-truncated data, and other forms of...

Read the rest of this article with a Free Trial at HighBeam Research.

Premium Content Partnership | HighBeam Research provides an in-depth online archive library of reference works.