On the targets of inference with multivariate failure time data

Area of Science:

• Biostatistics
• Survival Analysis
• Epidemiology

Background:

• Multivariate failure time data analysis requires tailored methods for diverse research questions.
• Existing methods like marginal hazard models, copula models, and frailty models address specific aspects of failure time data.

Purpose of the Study:

• To describe recently proposed multivariate marginal hazard methods.
• To illustrate the application of these methods using real-world data.

Main Methods:

• Overview of marginal hazard rate models for individual outcomes.
• Description of semiparametric copula models for dependency analysis.
• Explanation of frailty models for clustered failure times.
• Introduction to multivariate marginal hazard methods for multi-dimensional analysis.

Main Results:

• The study details various multivariate failure time regression approaches.
• It demonstrates the utility of multivariate marginal hazard methods.

Conclusions:

• The choice of multivariate failure time analysis method depends on the specific research focus.
• Multivariate marginal hazard methods offer a powerful tool for exploring exposures in relation to multi-dimensional hazard rates.