Combined estimating equation approaches for the additive hazards model with left-truncated and interval-censored data

Tianyi Lu, Shuwei Li () and Liuquan Sun
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Tianyi Lu: Guangzhou University
Shuwei Li: Guangzhou University
Liuquan Sun: Chinese Academy of Sciences

Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, 2023, vol. 29, issue 3, No 9, 672-697

Abstract: Abstract Interval-censored failure time data arise commonly in various scientific studies where the failure time of interest is only known to lie in a certain time interval rather than observed exactly. In addition, left truncation on the failure event may occur and can greatly complicate the statistical analysis. In this paper, we investigate regression analysis of left-truncated and interval-censored data with the commonly used additive hazards model. Specifically, we propose a conditional estimating equation approach for the estimation, and further improve its estimation efficiency by combining the conditional estimating equation and the pairwise pseudo-score-based estimating equation that can eliminate the nuisance functions from the marginal likelihood of the truncation times. Asymptotic properties of the proposed estimators are discussed including the consistency and asymptotic normality. Extensive simulation studies are conducted to evaluate the empirical performance of the proposed methods, and suggest that the combined estimating equation approach is obviously more efficient than the conditional estimating equation approach. We then apply the proposed methods to a set of real data for illustration.

Keywords: Additive hazards regression; Estimating equation; Interval censoring; Left truncation; Pairwise pseudo-likelihood (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s10985-023-09596-6

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