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Azhar Mehmood Abbasi1, Muhammad Yousaf Shad1

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Summary
This summary is machine-generated.

This study introduces concomitant-based rank set sampling (CRSS) for estimating sensitive proportions. CRSS offers a more precise, unbiased estimator than simple random sampling (SRS) without added cost.

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Area of Science:

  • Statistics
  • Survey Methodology

Background:

  • Estimating sensitive proportions accurately is crucial in surveys.
  • Simple random sampling (SRS) can be inefficient for sensitive data.
  • Existing methods may compromise respondent confidentiality.

Purpose of the Study:

  • To propose and evaluate the concomitant-based rank set sampling (CRSS) method.
  • To develop a new ratio-based estimator for sensitive proportions using CRSS.
  • To ensure respondent confidentiality while improving estimation precision.

Main Methods:

  • Concomitant-based rank set sampling (CRSS) procedure.
  • Development of a ratio-based estimator incorporating a randomizing device.
  • Numerical integration technique for evaluating estimator performance.
  • Application using real-world data.

Main Results:

  • CRSS provides an unbiased estimator for the population sensitive proportion.
  • CRSS is consistently more precise than SRS estimators.
  • The new ratio-based estimator maintains confidentiality.
  • Numerical and real-data applications validate the proposed methods.

Conclusions:

  • CRSS is an effective and efficient sampling technique for sensitive proportion estimation.
  • The new ratio-based estimator offers a confidential and precise alternative.
  • CRSS improves upon traditional SRS methods in terms of precision and cost-effectiveness.