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

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Author Info

  • Marc Höglinger

    ()

  • Ben Jann

    ()

  • Andreas Diekmann

    ()

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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 (CM) 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 and the CM 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. The results reveal a poor performance of the forced-response RRT, while the CM yielded significantly higher estimates of sensitive behaviors than direct questioning. We conclude that the CM is a promising approach for asking sensitive questions in self-administered surveys.

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Bibliographic Info

Paper provided by University of Bern, Department of Social Sciences in its series University of Bern Social Sciences Working Papers with number 9.

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Length: 51 pages
Date of creation: 22 May 2014
Date of revision: 24 Jun 2014
Handle: RePEc:bss:wpaper:9

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Web page: http://www.sowi.unibe.ch/

Related research

Keywords: online survey; sensitive questions; plagiarism; exam cheating; randomized response technique; crosswise model;

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Cited by:
  1. 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.

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