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Cross-ratio estimation for bivariate failure times with left truncation
Authors:Tianle Hu  Xihong Lin  Bin Nan
Affiliation:1. Eli Lilly and Company, Indianapolis, IN, 6285, USA
2. Department of Biostatistics, Harvard School of Public Health, Boston, MA, 02115, USA
3. Department of Biostatistics, University of Michigan, Ann Arbor, MI, 48109, USA
Abstract:
The cross-ratio is an important local measure that characterizes the dependence between bivariate failure times. To estimate the cross-ratio in follow-up studies where delayed entry is present, estimation procedures need to account for left truncation. Ignoring left truncation yields biased estimates of the cross-ratio. We extend the method of Hu et al., Biometrika 98:341–354 (2011) by modifying the risk sets and relevant indicators to handle left-truncated bivariate failure times, which yields the cross-ratio estimate with desirable asymptotic properties that can be shown by the same techniques used in Hu et al., Biometrika 98:341–354 (2011). Numerical studies are conducted.
Keywords:
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