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A Pairwise Likelihood Augmented Estimator For The Cox Model Under Left-Truncation, Fan Wu, Sehee Kim, Jing Qin, Rajiv Saran, Yi Li

The University of Michigan Department of Biostatistics Working Paper Series

Survival data collected from prevalent cohorts are subject to left-truncation and the analysis is challenging. Conditional approaches for left-truncated data under the Cox model are inefficient as they typically ignore the information in the marginal likelihood of the truncation times. Length-biased sampling methods can improve the estimation efficiency but only when the stationarity assumption of the disease incidence holds, i.e., the truncation distribution is uniform; otherwise they may generate biased estimates. In this paper, we propose a semi-parametric method for the Cox model under general left-truncation, where the truncation distribution is unspecified. Our approach is to make inference based on …