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Computing the Cox model for case cohort designs.

T M Therneau1, H Li

  • 1Section of Biostatistics, Mayo Foundation, Rochester, MN 55905, USA. therneau.terry@mayo.edu

Lifetime Data Analysis
|July 17, 1999
PubMed
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This study details efficient case-cohort designs for survival analysis, offering practical methods for estimating covariate effects. It demonstrates how to implement these advanced statistical techniques using common software packages like SAS and S-Plus.

Area of Science:

  • Biostatistics
  • Survival Analysis
  • Epidemiology

Background:

  • The case-cohort design, introduced by Prentice (1986), is a valuable subsampling strategy for survival studies.
  • Subsequent research has developed a family of related sampling plans and estimators for covariate effects.

Purpose of the Study:

  • To provide practical guidance on obtaining parameter and variance estimates for case-cohort designs.
  • To illustrate the implementation of these methods using standard statistical software.

Main Methods:

  • The study focuses on the application of case-cohort designs and associated estimators.
  • It demonstrates the procedural steps for calculating estimates within statistical software.

Main Results:

Related Experiment Videos

  • The paper outlines how to compute parameter estimates derived from case-cohort studies.
  • It details the process for obtaining variance estimates for these parameters.

Conclusions:

  • Case-cohort designs offer an efficient approach to survival data analysis.
  • Standard statistical software packages, such as SAS and S-Plus, can be effectively utilized for implementing these methods.