A Joint Model of Competing Risks in Discrete Time with Longitudinal Information

Abstract

The survival competing risks model in discrete time based on multinomial logistic regression, proposed by Luo et al. (2016), models the non-linear and irregular shape of hazard functions by incorporating a time-dependent spline into the multinomial logistic regression. This model also directly includes longitudinal variables in the regression. Due to the issues arising from including both baseline and longitudinal covariates in the extended form as proposed, and considering that the latter may be subject to error, this article suggests an extension of the existing model. The proposed extension utilizes the concept of joint models for longitudinal and survival data, which is an effective approach for integrating simultaneousness both baseline and time-dependent covariates into the survival model.,