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Sample size determination in shared frailty models for multivariate time-to-event data.

Liddy M Chen1, Joseph G Ibrahim, Haitao Chu

  • 1a Global Research Operation, Biostatistics, PAREXEL International , Durham , North Carolina , USA.

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Summary
This summary is machine-generated.

This study introduces a new sample size calculation method for shared frailty models, essential for analyzing complex time-to-event data in clinical trials. The developed method aids researchers in designing robust studies investigating treatment effects on multiple events.

Keywords:
Frailty modelMultivariate survivalSample size

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Area of Science:

  • Biostatistics
  • Clinical Trial Design
  • Survival Analysis

Background:

  • Multivariate time-to-event data analysis is crucial in clinical research.
  • Shared frailty models are widely used for such data.
  • Existing literature lacks methods for sample size determination in these complex study designs.

Purpose of the Study:

  • To develop a novel sample size determination method for shared frailty models.
  • To investigate the treatment effect on multivariate event times.
  • To address the gap in sample size calculation methodologies for complex survival data.

Main Methods:

  • Developed a sample size determination method tailored for shared frailty models.
  • Utilized both parametric and piecewise models with unknown baseline hazards for data analysis.
  • Compared empirical power against calculated power to validate the method.

Main Results:

  • The proposed sample size method was developed and applied.
  • Empirical power was compared with calculated power, demonstrating the method's utility.
  • Formulas for testing treatment effects on recurrent events were discussed.

Conclusions:

  • A practical sample size determination method for shared frailty models is now available.
  • This contributes to improved study design for multivariate time-to-event data.
  • The findings support more rigorous clinical trial planning and analysis.