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<p>Ranked set sampling (RSS) is an important survey technique aimed at efficient estimation of population characteristics. Various RSS methods can be used to collect an RSS sample, but the reproducibility of estimates using these methods remains unexplored. Reproducibility refers to obtaining similar estimates when the survey is repeated under identical conditions. This study compares the reproducibility of population mean estimates using four basic RSS methods: classical RSS (RSS), Median RSS (MRSS), Extreme RSS (ERSS), and Paired RSS (PRSS). We assess the reproducibility of these methods using Nonparametric Predictive Inference (NPI) bootstrapping. Simulations are conducted for varying sample sizes with both perfect and imperfect rankings, and results are compared for weak and strong associations between the study and concomitant variables. Additionally, we apply these methods to agricultural data from Punjab, India. Our findings indicate that MRSS provides the best reproducibility for population mean estimates, while ERSS performs the worst in this regard.</p>

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Comparative Study of Reproducibility of Ranked Set Sampling Methods using Predictive Inference

  • 期刊论文

  • 发表日期：

    2026年3月3日

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  • Syed Abdul Rehman,
  • Tahani Coolen-Maturi,
  • Frank P. A. Coolen,
  • Javid Shabbir

摘要

Ranked set sampling (RSS) is an important survey technique aimed at efficient estimation of population characteristics. Various RSS methods can be used to collect an RSS sample, but the reproducibility of estimates using these methods remains unexplored. Reproducibility refers to obtaining similar estimates when the survey is repeated under identical conditions. This study compares the reproducibility of population mean estimates using four basic RSS methods: classical RSS (RSS), Median RSS (MRSS), Extreme RSS (ERSS), and Paired RSS (PRSS). We assess the reproducibility of these methods using Nonparametric Predictive Inference (NPI) bootstrapping. Simulations are conducted for varying sample sizes with both perfect and imperfect rankings, and results are compared for weak and strong associations between the study and concomitant variables. Additionally, we apply these methods to agricultural data from Punjab, India. Our findings indicate that MRSS provides the best reproducibility for population mean estimates, while ERSS performs the worst in this regard.