吉林大学学报(理学版) ›› 2026, Vol. 64 ›› Issue (5): 949-0957.

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区间删失数据下广义指数比例风险模型的因果效应估计

王淑影1, 董贺1, 高洋1, 赵世舜2   

  1. 1. 长春工业大学 数学与统计学院, 长春 130012; 2. 吉林大学 数学学院, 长春 130012
  • 收稿日期:2025-11-19 出版日期:2026-09-26 发布日期:2026-09-26
  • 通讯作者: 董贺 E-mail:125014070@qq.com

Estimation of  Causal  Effects of Generalized Exponential Proportional Hazards Model under Interval-Censored Data

Wang Shuying1, Dong He1, Gao Yang1, Zhao Shishun2   

  1. 1. School of Mathematics and Statistics, Changchun University of Technology, Changchun 130012, China;
    2. College of Mathematics, Jilin University, Changchun 130012, China
  • Received:2025-11-19 Online:2026-09-26 Published:2026-09-26

摘要: 首先, 针对存在未测量混杂和治疗不依从的区间Ⅰ型删失数据因果效应估计问题, 将工具变量与广义指数比例风险模型相结合, 采用极大似然方法估计依从者中的因果治疗效应. 其次, 用模拟实验结果验证该方法的有效性. 最后, 将该方法应用于HIP乳腺癌筛查临床试验数据验证其有效性.

关键词: 工具变量, 区间删失数据, 广义指数比例风险模型, 因果效应, 极大似然估计

Abstract: Firstly, aiming at the problem of  estimation of  causal effects in interval Ⅰtype censored data with unmeasured confounding and treatment noncompliance, we  combined instrumental variables with the generalized exponential proportional hazards model and used the maximum likelihood method to estimate the causal treatment effect among compliers. Secondly, the simulation experiment results verified the effectiveness of the proposed method. Finally, the  proposed method was applied to clinical trial data of the HIP breast cancer screening to verify its effectiveness.

Key words: instrumental variable, interval-censored data, generalized exponential proportional hazards model, causal effect, maximum likelihood estimation

中图分类号: 

  • O212