IDEAS home Printed from https://ideas.repec.org/a/eee/csdana/v77y2014icp157-169.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167947314000590
    Download Restriction: Full text for ScienceDirect subscribers only.
    File URL: https://libkey.io/10.1016/j.csda.2014.02.019?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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. 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.
    3. 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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Andreas Lagerås & Mathias Lindholm, 2020. "How to ask sensitive multiple‐choice questions," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 47(2), pages 397-424, June.
    2. Guo-Liang Tian, 2014. "A new non-randomized response model: The parallel model," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 68(4), pages 293-323, November.
    3. Raghunath Arnab & Dahud Kehinde Shangodoyin & Antonio Arcos, 2019. "Nonrandomized Response Model For Complex Survey Designs," Statistics in Transition New Series, Polish Statistical Association, vol. 20(1), pages 67-86, March.
    4. Liu, Yin & Tian, Guo-Liang, 2013. "A variant of the parallel model for sample surveys with sensitive characteristics," Computational Statistics & Data Analysis, Elsevier, vol. 67(C), pages 115-135.
    5. Heiko Groenitz, 2015. "Using prior information in privacy-protecting survey designs for categorical sensitive variables," Statistical Papers, Springer, vol. 56(1), pages 167-189, February.
    6. Truong-Nhat Le & Shen-Ming Lee & Phuoc-Loc Tran & Chin-Shang Li, 2023. "Randomized Response Techniques: A Systematic Review from the Pioneering Work of Warner (1965) to the Present," Mathematics, MDPI, vol. 11(7), pages 1-26, April.
    7. Heiko Groenitz, 2014. "A new privacy-protecting survey design for multichotomous sensitive variables," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 77(2), pages 211-224, February.
    8. Carlos Barros, 2012. "Sustainable Tourism in Inhambane-Mozambique," CEsA Working Papers 105, CEsA - Centre for African and Development Studies.
    9. Burgstaller, Lilith & Feld, Lars P. & Pfeil, Katharina, 2022. "Working in the shadow: Survey techniques for measuring and explaining undeclared work," Journal of Economic Behavior & Organization, Elsevier, vol. 200(C), pages 661-671.
    10. Kazuo Yamaguchi, 2016. "Cross-sectional and Panel Data Analyses of an Incompletely Observed Variable Derived From the Nonrandomized Method for Surveying Sensitive Questions," Sociological Methods & Research, , vol. 45(1), pages 41-68, February.
    11. Pavel Dietz & Anne Quermann & Mireille Nicoline Maria van Poppel & Heiko Striegel & Hannes Schröter & Rolf Ulrich & Perikles Simon, 2018. "Physical and cognitive doping in university students using the unrelated question model (UQM): Assessing the influence of the probability of receiving the sensitive question on prevalence estimation," PLOS ONE, Public Library of Science, vol. 13(5), pages 1-12, May.
    12. Horng-Jinh Chang & Mei-Pei Kuo, 2012. "Estimation of population proportion in randomized response sampling using weighted confidence interval construction," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 75(5), pages 655-672, July.
    13. Pier Francesco Perri & Eleni Manoli & Tasos C. Christofides, 2023. "Assessing the effectiveness of indirect questioning techniques by detecting liars," Statistical Papers, Springer, vol. 64(5), pages 1483-1506, October.
    14. Blume, Andreas & Lai, Ernest K. & Lim, Wooyoung, 2019. "Eliciting private information with noise: The case of randomized response," Games and Economic Behavior, Elsevier, vol. 113(C), pages 356-380.
    15. Marc Höglinger & Ben Jann, 2018. "More is not always better: An experimental individual-level validation of the randomized response technique and the crosswise model," PLOS ONE, Public Library of Science, vol. 13(8), pages 1-22, August.
    16. Isabel Thielmann & Daniel W. Heck & Benjamin E. Hilbig, 2016. "Anonymity and incentives: An investigation of techniques to reduce socially desirable responding in the Trust Game," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 11(5), pages 527-536, September.
    17. John, Leslie K. & Loewenstein, George & Acquisti, Alessandro & Vosgerau, Joachim, 2018. "When and why randomized response techniques (fail to) elicit the truth," Organizational Behavior and Human Decision Processes, Elsevier, vol. 148(C), pages 101-123.
    18. Carlos Barros & Vera Barros & Peter Dieke, 2012. "Tourism and Human Development in Mozambique: an analysis for Inhambane province," CEsA Working Papers 100, CEsA - Centre for African and Development Studies.
    19. Bernard GAUTHIER & Frédéric LESNÉ, 2017. "Measuring corruption in presence of reticent respondents: Theory and Application," Working Papers P207, FERDI.
    20. Shen-Ming Lee & Phuoc-Loc Tran & Truong-Nhat Le & Chin-Shang Li, 2023. "Prediction of a Sensitive Feature under Indirect Questioning via Warner’s Randomized Response Technique and Latent Class Model," Mathematics, MDPI, vol. 11(2), pages 1-21, January.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:csdana:v:77:y:2014:i:c:p:157-169. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/csda .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.