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Sensitive Questions in Online Surveys: An Experimental Evaluation of the Randomized Response Technique and the Crosswise Model

Author

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  • Marc Höglinger
  • Ben Jann
  • Andreas Diekmann

Abstract

Self-administered online surveys provide a higher level of privacy protection to respondents than surveys administered by an interviewer. Yet, studies indicate that asking sensitive questions is problematic also in self-administered surveys. Because respondents might not be willing to reveal the truth and provide answers that are subject to social desirability bias, the validity of prevalence estimates of sensitive behaviors from online surveys can be challenged. A well-known method to overcome these problems is the Randomized Response Technique (RRT). However, convincing evidence that the RRT provides more valid estimates than direct questioning in online surveys is still lacking. A new variant of the RRT called the Crosswise Model has recently been proposed to overcome some of the deficiencies of existing RRT designs. We therefore conducted an experimental study in which different implementations of the RRT, including two implementations of the crosswise model, were tested and compared to direct questioning. Our study is a large-scale online survey (N = 6,037) on sensitive behaviors by students such as cheating in exams and plagiarism. Results indicate that the crosswise-model RRT---unlike the other variants of RRT we evaluated---yields higher prevalence estimates of sensitive behaviors than direct questioning. Whether higher estimates are a sufficient condition for more valid results, however, remains questionable.

Suggested Citation

  • Marc Höglinger & Ben Jann & Andreas Diekmann, 2014. "Sensitive Questions in Online Surveys: An Experimental Evaluation of the Randomized Response Technique and the Crosswise Model," University of Bern Social Sciences Working Papers 9, University of Bern, Department of Social Sciences, revised 24 Jun 2014.
  • Handle: RePEc:bss:wpaper:9
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    Citations

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    Cited by:

    1. Andreas Quatember, 2019. "A discussion of the two different aspects of privacy protection in indirect questioning designs," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(1), pages 269-282, January.
    2. Korndörfer, Martin & Krumpal, Ivar & Schmukle, Stefan C., 2014. "Measuring and explaining tax evasion: Improving self-reports using the crosswise model," Journal of Economic Psychology, Elsevier, vol. 45(C), pages 18-32.
    3. 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.
    4. 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.
    5. Kundt, Thorben, 2014. "Applying “Benford’s law” to the Crosswise Model: Findings from an online survey on tax evasion," Working Paper 148/2014, Helmut Schmidt University, Hamburg.
    6. Kirchner Antje, 2015. "Validating Sensitive Questions: A Comparison of Survey and Register Data," Journal of Official Statistics, Sciendo, vol. 31(1), pages 31-59, March.

    More about this item

    Keywords

    online survey; sensitive questions; plagiarism; exam cheating; randomized response technique; crosswise model;
    All these keywords.

    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods

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