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A variant of the parallel model for sample surveys with sensitive characteristics

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  • Liu, Yin
  • Tian, Guo-Liang

Abstract

A new non-randomized response (NRR) model (called a variant of the parallel model) is proposed. The survey design and corresponding statistical inferences including likelihood-based methods, Bayesian methods and bootstrap methods are provided. Theoretical and numerical comparisons showed that the proposed variant of the parallel model over-performs two existing NRR crosswise and triangular models for most of the possible parameter ranges. An outline for handling the possible non-compliance behavior in the proposed model is provided. An illustrative example from an existing survey on ‘sexual practices’ in San Francisco, Las Vegas and Portland is used to demonstrate the proposed statistical analysis methods. Two real surveys on the cheating behavior in examinations at the University of Hong Kong are conducted and are used to illustrate the proposed design and analysis methods.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:csdana:v:67:y:2013:i:c:p:115-135
    DOI: 10.1016/j.csda.2013.05.003
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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.
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    3. Tasos Christofides, 2005. "Randomized response technique for two sensitive characteristics at the same time," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 62(1), pages 53-63, September.
    4. 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.
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    6. Guo‐Liang Tian & Ming Tan & Kai Wang Ng, 2007. "An exact non‐iterative sampling procedure for discrete missing data problems," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 61(2), pages 232-242, May.
    7. Elisabeth Coutts & Ben Jann, 2011. "Sensitive Questions in Online Surveys: Experimental Results for the Randomized Response Technique (RRT) and the Unmatched Count Technique (UCT)," Sociological Methods & Research, , vol. 40(1), pages 169-193, February.
    8. Ardo van den Hout & Ulf Böckenholt & Peter G. M. Van Der Heijden, 2010. "Estimating the prevalence of sensitive behaviour and cheating with a dual design for direct questioning and randomized response," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 59(4), pages 723-736, August.
    9. Xiangen Hu & William Batchelder, 1994. "The statistical analysis of general processing tree models with the EM algorithm," Psychometrika, Springer;The Psychometric Society, vol. 59(1), pages 21-47, March.
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    Cited by:

    1. Yin Liu & Guo-Liang Tian & Qin Wu & Man-Lai Tang, 2019. "Poisson–Poisson item count techniques for surveys with sensitive discrete quantitative data," Statistical Papers, Springer, vol. 60(5), pages 1763-1791, October.
    2. Heiko Groenitz, 2017. "Valid estimates for repeated randomized response methods," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(16), pages 2994-3010, December.

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