A0572
Title: Accelerated failure time model with a semiparametric skewed error distribution
Authors: Byungtae Seo - Sungkyunkwan University (Korea, South) [presenting]
Abstract: The accelerated failure time (AFT) model is widely used to analyze relationships between variables in survival analysis. However, this model often relies on parametric error distribution, which can lead to biased or inefficient estimates if this assumption is violated. In order to overcome this challenge, it is proposed to use a semiparametric skew-normal scale mixture distribution for the error term in the AFT model. This approach reduces the risk of misspecification and improves the accuracy of parameter estimation. The identifiability and consistency of the proposed model are investigated, and a practical estimation algorithm is developed. To evaluate the performance of the approach, extensive simulation studies and real data analyses are conducted. The results demonstrate the effectiveness of the method in providing robust and accurate estimates in various scenarios.
