Refinement of the extended crosswise model with a number sequence randomizer: Evidence from three different studies in the UK

Khadiga H A Sayed, Maarten J L F Cruyff, Peter G M van der Heijden and Andrea Petróczi

PLOS ONE, 2022, vol. 17, issue 12, 1-19

Abstract: The Extended Crosswise Model (ECWM) is a randomized response model with neutral response categories, relatively simple instructions, and the availability of a goodness-of-fit test. This paper refines this model with a number sequence randomizer that virtually precludes the possibility to give evasive responses. The motivation for developing this model stems from a strategic priority of WADA (World Anti-Doping Agency) to monitor the prevalence of doping use by elite athletes. For this model we derived a maximum likelihood estimator that allows for binary logistic regression analysis. Three studies were conducted on online platforms with a total of over 6, 000 respondents; two on controlled substance use and one on compliance with COVID-19 regulations in the UK during the first lockdown. The results of these studies are promising. The goodness-of-fit tests showed little to no evidence for response biases, and the ECWM yielded higher prevalence estimates than direct questions for sensitive questions, and similar ones for non-sensitive questions. Furthermore, the randomizer with the shortest number sequences yielded the smallest response error rates on a control question with known prevalence.

Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0279741

DOI: 10.1371/journal.pone.0279741

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