On Kernel-Based Estimator of Odds Ratio Using Different Stratified Sampling Schemes

Abbas Eftekharian, Hani Samawi, Haresh Rochani

Research output: Contribution to journalArticlepeer-review

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Abstract

The kernel-based estimator of Cochran Mantel-Haenszel odds ratio based on stratified simple and ranked set sampling is proposed. The expectation and variance of the estimator are analytically obtained. Using a simulation study, the estimator based on stratified ranked set sampling is more efficient than its counterpart based on stratified simple random sampling. Finally, the estimator's performance is investigated by using base deficit data.

Original languageAmerican English
Pages (from-to)368-389
Number of pages22
JournalStatistics, Optimization Information Computing
Volume11
Issue number2
DOIs
StatePublished - Dec 22 2022

Scopus Subject Areas

  • Signal Processing
  • Statistics and Probability
  • Information Systems
  • Computer Vision and Pattern Recognition
  • Statistics, Probability and Uncertainty
  • Control and Optimization
  • Artificial Intelligence

Disciplines

  • Biostatistics
  • Epidemiology

Keywords

  • Cochran Mantel-Haenszel odds ratio
  • Kernel estimation
  • Odds ratio
  • Stratified ranked set sampling
  • Stratified simple random sampling

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