A0498
Title: Change-point detection of time-varying Cox model
Authors: Kaimeng Zhang - Innovation Center of Yangtze River Delta;Zhejiang University (China) [presenting]
Chi Tim Ng - Hang Seng University of Hong Kong (Hong Kong)
Abstract: A novel Cox model is presented that incorporates time-varying coefficients for time-dependent survival analysis. Transformable penalized likelihood estimation is employed to address the challenge of change point detection in the proposed model. The asymptotic properties of the local solutions are established, and numerical studies are conducted to demonstrate the effectiveness of the proposed approach. The efficacy of the method is illustrated through the analysis of data from the Rossi dataset. Overall, the research contributes to the advancement of time-dependent survival analysis by introducing a robust and efficient methodology with potential applications in various fields, including medicine and engineering.
