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Parameter Estimation in Stratified Cluster Sampling under Randomized Response Models for Sensitive Question Survey.

Xiangke Pu1, Ge Gao2, Yubo Fan2

  • 1Institute of Hepatology, Changzhou Third People's Hospital, Changzhou, Jiangsu Province, 213001, P.R. China.

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|February 18, 2016
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Summary
This summary is machine-generated.

This study introduces new formulas for sensitive survey questions using cluster sampling. These advanced methods improve data accuracy for sensitive topics in large populations.

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Area of Science:

  • Survey Methodology
  • Statistics
  • Social Science Research

Background:

  • Randomized response models enhance accuracy for sensitive survey questions.
  • Simple random sampling is common but impractical for large populations.
  • Advanced sampling techniques are underutilized in sensitive surveys.

Purpose of the Study:

  • To develop parameter estimation formulas for cluster and stratified cluster sampling under randomized response models.
  • To evaluate the performance of these new methods in real-world sensitive surveys.

Main Methods:

  • Utilized classic sampling theories and total probability formulas.
  • Developed formulas for cluster sampling and stratified cluster sampling.
  • Applied models to surveys on premarital sex and exam cheating.

Main Results:

  • The developed formulas provide reliable parameter estimation for sensitive questions.
  • Demonstrated high reliability of the proposed survey methods and formulas.
  • Successfully applied methods to a university population.

Conclusions:

  • The new formulas and methods are effective for sensitive question surveys.
  • Cluster and stratified cluster sampling with randomized response offer reliable solutions.
  • These techniques are suitable for large-scale sensitive data collection.