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Pseudo-likelihood estimation for a marginal multivariate survival model.

Fabián Tibaldi1, Geert Molenberghs, Tomasz Burzykowski

  • 1Center for Statistics, Limburgs Universitair Centrum, Transnationale Universiteit Limburg, Diepenbeek Universitaire Campus, B3590 Diepenbeek, Belgium. fabian.tibaldi@luc.ac.be

Statistics in Medicine
|March 18, 2004
PubMed
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We introduce a new multivariate Plackett-Dale model to analyze survival data, offering a novel approach for understanding time-to-event outcomes in complex scenarios like disease progression and genetic studies.

Area of Science:

  • Biostatistics
  • Survival Analysis
  • Population Genetics

Background:

  • Survival outcomes are crucial in many fields, including medicine and genetics.
  • Existing models may not fully capture complex associations in survival data.
  • The Plackett-Dale model offers a framework for dependent survival times.

Purpose of the Study:

  • To propose a novel multivariate Plackett-Dale model for analyzing survival outcomes.
  • To develop a pseudo-likelihood estimation method for model parameters.
  • To demonstrate the model's applicability through diverse case studies.

Main Methods:

  • Development of a multivariate Plackett-Dale model.
  • Application of a pseudo-likelihood estimation technique.
  • Case study analysis in HIV/AIDS and population genetics.

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Main Results:

  • The proposed model effectively analyzes multivariate survival data.
  • Pseudo-likelihood estimation provides reliable parameter estimates.
  • Successful application in modeling survival times in AIDS and adoption data.

Conclusions:

  • The multivariate Plackett-Dale model is a valuable tool for survival analysis.
  • The methodology is adaptable to various fields, including epidemiology and genetics.
  • This approach enhances the understanding of associated survival times.