A Tobit Partly Linear Mixed and Mixture Cure Model for the Joint Analysis of Interval‐Bounded Longitudinal Measurements and Survival Times With Cure Proportion

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Authors: Zhanfeng Wang, Zerui Shen, Ruixing Ming, Dongsheng Tu
Cited by: 0
References: 15

Abstract

Motivated by the analysis of data from a clinical trial on patients with early breast cancer, we propose in this paper a new joint model that uses a Tobit partly linear mixed model for longitudinal measurements which are bounded in an interval and have a nonlinear relationship with the observation times and a semiparametric mixture cure model that incorporates a B-spline baseline hazard for survival times with cure proportion. A procedure is developed for estimating parameters in the proposed model using the partial likelihood and Laplace approximation. Additionally, a method of random weighting is proposed to compute the variances of the parameter estimators. The performance of the proposed model and the inference procedures is evaluated through simulation studies and data from the clinical trial that motivated this study.

Fields of Study & Subjects

Statistical Methods and Bayesian Inference Statistical Distribution Estimation and Applications Statistical Methods in Clinical Trials

Publication details

Journal / source
Pharmaceutical Statistics
Volume
25
Issue
2
Pages
e70072–e70072
Publication date
30 January 2026
Language
EN