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Analysis of Survival Data under Competing Risks with Missing Cause of Death Information: Application and Implications for Study Design

In: Lifetime Data: Models in Reliability and Survival Analysis

Author

Listed:
  • Janet W. Andersen

    (Harvard School of Public Health, Dana Farber Cancer Institute)

  • Els J. Goetghebeur

    (Limburgs Universitair Centrum)

  • Louise Ryan

    (Harvard School of Public Health, Dana Farber Cancer Institute)

Abstract

Goetghebeur and Ryan have developed a method for multiple-covariate analyses of survival data subject to competing risks when the failure type is missing for some cases. This method is compared to standard techniques over a range of missingness in failure type in a Hodgkin’s Disease data set and found to provide regression coefficients and inferences which were less biased than those from other methods.

Suggested Citation

  • Janet W. Andersen & Els J. Goetghebeur & Louise Ryan, 1996. "Analysis of Survival Data under Competing Risks with Missing Cause of Death Information: Application and Implications for Study Design," Springer Books, in: Nicholas P. Jewell & Alan C. Kimber & Mei-Ling Ting Lee & G. A. Whitmore (ed.), Lifetime Data: Models in Reliability and Survival Analysis, pages 13-19, Springer.
  • Handle: RePEc:spr:sprchp:978-1-4757-5654-8_3
    DOI: 10.1007/978-1-4757-5654-8_3
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