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An additive-multiplicative rates model for recurrent event data with informative terminal event
1Institute of Applied Mathematics, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, People's Republic of China. slq@amt.ac.cn
Lifetime Data Analysis
|September 12, 2012
Summary
This study introduces a new statistical model for analyzing repeated health events alongside a final event like death. The model nonparametrically links these events, offering a robust method for survival analysis.
Area of Science:
- Biostatistics
- Survival Analysis
- Epidemiology
Background:
- Recurrent event data analysis is crucial in medical research.
- Terminal events, such as death, often influence recurrent event processes.
- Existing models may not fully capture the complex interplay between recurrent and terminal events.
Purpose of the Study:
- To propose a novel additive-multiplicative rates model for recurrent event data.
- To account for the presence of a terminal event (e.g., death).
- To nonparametrically model the association between recurrent and terminal events.
Main Methods:
- Development of estimating equation approaches for parameter inference.
- Establishment of asymptotic properties for the proposed estimators.
- Evaluation of finite sample performance via simulation studies.
Main Results:
- The proposed additive-multiplicative rates model provides a flexible framework.
- Nonparametric association modeling enhances the analysis of recurrent and terminal events.
- Simulation studies confirm the validity and efficiency of the estimators.
Conclusions:
- The new model offers a valuable tool for analyzing complex event data in medical studies.
- The methodology is applicable to various research areas, including clinical trials and epidemiological research.
- Demonstrated utility through an application to a bladder cancer study.
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