Abstract: We proposed a semi-parametric accelerated hazard regression model with measurement errors based on the current status data. Firstly, the unknown baseline cumulative hazard function was approximated by using I-spline, and parameter estimates of the model were obtained based on Sieve maximum likelihood estimation method. Secondly, a simulation extrapolation method was used to correct  estimation error caused by  measurement errors in covariates. Thirdly, the numerical simulations were carried out to verify the effectiveness of the proposed method as well as the impact of ignoring measurement error in covariates. Finally,  the proposed method was applied to study cardiovascular and cerebrovascular disease mortality, we obtained estimation of hazard function for  cardiovascular and cerebrovascular disease mortality. The experimental results show that the proposed method is effective.

Key words: accelerated hazard model, simulation extrapolation, measurement error, maximum likelihood estimate, I-spline