Title: Analysis of proportional mean residual life model with latent variables
Authors: Xinyuan Song - Chinese University of Hong Kong (Hong Kong) [presenting]
Abstract: End-stage renal disease (ESRD) is one of the most serious diabetes complications. Numerous studies have been devoted to revealing the risk factors of the onset time of ESRD. We propose a proportional mean residual life (MRL) model with latent variables to assess the effects of observed and latent risk factors on MRL function of ESRD in a cohort of Chinese type 2 diabetic patients. The proposed model generalizes conventional proportional MRL model to accommodate latent risk factors and right censored data. We employ a factor analysis model to characterize latent risk factors via multiple observed variables. We develop a borrow-strength estimation procedure, which incorporates the expectation-maximization algorithm and the corrected estimating equation approach. The asymptotic properties of the proposed estimators are established. Simulation shows that the performance of the proposed methodology is satisfactory. The application to the study of type 2 diabetes reveals insights into the prevention of ESRD.