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Journal article

Estimation of the average survival function using a censored data regression model.

Lifetime data analysis, vol. 6, issue 1 (2000) pp. 73-84

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Abstract

In the presence of covariates information, assuming the linear relationship between a transformation of survival time and covariates, we propose a new estimator of survival function and show its consistency. In addition, a comparison of the proposed estimator with the product-limit estimator introduced by Kaplan and Meier (1958) is performed through Monte Carlo simulation studies. We illustrate the proposed estimator with the updated Stanford heart transplant data.

Author-supplied keywords

  • Biometry
  • Heart Transplantation
  • Heart Transplantation: mortality
  • Humans
  • Linear Models
  • Monte Carlo Method
  • Survival Analysis

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Authors

  • J Kim

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