ArticlePloS one2022
Refinement of the extended crosswise model with a number sequence randomizer: Evidence from three different studies in the UK.
Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Doping Prevalence in Sport from Indirect Estimation Models: A Systematic Review and Meta-analysis.Sports medicine - open · 2026Pooled it
- Charting the Scientific Landscape of Indirect Estimation Models in Doping Prevalence Research: A Bibliometric Analysis with Narrative Appraisal.Sports (Basel, Switzerland) · 2026Review
- Modeling Evasive Response Bias in Randomized Response: Cheater Detection Versus Self-protective No-Saying.Psychometrika · 2024Article
- Prevalence estimates for COVID-19-related health behaviors based on the cheating detection triangular model.BMC public health · 2024Article
- The Crosswise Model for Surveys on Sensitive Topics: A General Framework for Item Selection and Statistical Analysis.Psychometrika · 2024Article
- The analysis of randomized response "ever" and "last year" questions: A non-saturated Multinomial model.Behavior research methods · 2024Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.