区间删失数据下广义指数比例风险模型的因果效应估计

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

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.

Abstract

Firstly, aiming at the problem of estimation of causal effects in interval Ⅰ type 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.

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

Key words

instrumental variable / interval-censored data / generalized exponential proportional hazards model / causal effect / maximum likelihood estimation

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基金资助

吉林省“长白英才计划”青年博士后项目(自然科学类)(202442110)