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

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.

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Publication Details

Journal
Pharmaceutical Statistics
Published
2026-01-30
DOI
https://doi.org/10.1002/pst.70072
Primary Topic
Bayesian Methods and Mixture Models
Type
article
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article

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

Dongsheng Tu, Ruixing Ming, Zerui Shen, Zhanfeng Wang
Pharmaceutical Statistics
Bayesian Methods and Mixture Models
article

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

Dongsheng Tu, Ruixing Ming, Zerui Shen, Zhanfeng Wang
article en

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.

Pharmaceutical StatisticsVol. 25(2)
University of Science and Technology of China (CN), Hefei University of Technology (CN), Queen's University (CA), Zhejiang Gongshang University (CN)
Openalex Percentile: Top 74%
Bayesian Methods and Mixture Models
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