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Sample size determination for estimating prevalence and a difference between two prevalences of sensitive attributes using the non-randomized triangular design

Author

Listed:
  • Qiu, Shi-Fang
  • Zou, G.Y.
  • Tang, Man-Lai

Abstract

A non-randomized triangular design has been shown to be more efficient than the conventional random response model in estimating the prevalence of sensitive attributes in surveys. Since most surveys focus on estimation, herein we derive sample size formulas for estimation of prevalence and a difference between two prevalences in this design. In contrast to the conventional approach to sample size estimation, we explicitly incorporate into the formulas an assurance probability of achieving the pre-specified precision. Exact evaluation results demonstrate that these formulas perform well. The methods are illustrated using data from a real study.

Suggested Citation

  • Qiu, Shi-Fang & Zou, G.Y. & Tang, Man-Lai, 2014. "Sample size determination for estimating prevalence and a difference between two prevalences of sensitive attributes using the non-randomized triangular design," Computational Statistics & Data Analysis, Elsevier, vol. 77(C), pages 157-169.
    • Handle: RePEc:eee:csdana:v:77:y:2014:i:c:p:157-169
    DOI: 10.1016/j.csda.2014.02.019
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    References listed on IDEAS

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    1. Tan, Ming T. & Tian, Guo-Liang & Tang, Man-Lai, 2009. "Sample Surveys With Sensitive Questions: A Nonrandomized Response Approach," The American Statistician, American Statistical Association, vol. 63(1), pages 9-16.
    2. Jun-Wu Yu & Guo-Liang Tian & Man-Lai Tang, 2008. "Two new models for survey sampling with sensitive characteristic: design and analysis," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 67(3), pages 251-263, April.
    3. Gerty J. L. M. Lensvelt-Mulders & Joop J. Hox & Peter G. M. van der Heijden & Cora J. M. Maas, 2005. "Meta-Analysis of Randomized Response Research," Sociological Methods & Research, , vol. 33(3), pages 319-348, February.
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