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