Further Increasing Fisher's Information for Parameters of Association in Accelerated Failure Time Models via Double Extreme Ranks

Hani M. Samawi, Amal Helu, Haresh Rochani

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Double Extreme Ranked Set Sampling (DERSS) was first introduced by Samawi (2002) as a modification to the well-known Ranked Set Sampling (RSS) and Extreme Ranked Set Sampling (ERSS). In this article, we provide a modification to DERSS scheme with ranking based on an easy-to-evaluate baseline auxiliary variable known to be associated with survival time. We show that using the modified DERSS improves the performance of the Accelerated failure time (AFT) survival model and provides a more efficient estimator of the hazard ratio than that based on their counter parts simple random sample (SRS), RSS and ERSS. Our theoretical and simulation studies show the superiority of using the modified DERSS for AFT survival models compared with using SRS, RSS and ERSS. A numerical example based on Worcester Heart Attack Study is presented to illustrate the implementation of the DERSS.

Original languageAmerican English
JournalPakistan Journal of Statistics and Operation Research
Volume15
StatePublished - Aug 10 2019

DC Disciplines

  • Applied Statistics
  • Statistical Theory
  • Statistical Methodology
  • Statistical, Nonlinear, and Soft Matter Physics
  • Biostatistics
  • Statistical Models

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