Modeling Evasive Response Bias in Randomized Response: Cheater Detection Versus Self-protective No-Saying.

Autor:	Sayed KHA; Department of Methodology and Statistics, Utrecht University, Padualaan 14, 3584 CH, Utrecht, The Netherlands. k.h.a.sayed@uu.nl.; Department of Statistics, Faculty of Economics and Political Science, Cairo University, Cairo, Egypt. k.h.a.sayed@uu.nl., Cruyff MJLF; Department of Methodology and Statistics, Utrecht University, Padualaan 14, 3584 CH, Utrecht, The Netherlands., van der Heijden PGM; Department of Methodology and Statistics, Utrecht University, Padualaan 14, 3584 CH, Utrecht, The Netherlands.; Department of Social Statistics and Demography, University of Southampton, Southampton, UK.
Jazyk:	angličtina
Zdroj:	Psychometrika [Psychometrika] 2024 Dec; Vol. 89 (4), pp. 1261-1279. Date of Electronic Publication: 2024 Aug 30.
DOI:	10.1007/s11336-024-10000-x
Abstrakt:	Randomized response is an interview technique for sensitive questions designed to eliminate evasive response bias. Since this elimination is only partially successful, two models have been proposed for modeling evasive response bias: the cheater detection model for a design with two sub-samples with different randomization probabilities and the self-protective no sayers model for a design with multiple sensitive questions. This paper shows the correspondence between these models, and introduces models for the new, hybrid "ever/last year" design that account for self-protective no saying and cheating. The model for one set of ever/last year questions has a degree of freedom that can be used for the inclusion of a response bias parameter. Models with multiple degrees of freedom are introduced for extensions of the design with a third randomized response question and a second set of ever/last year questions. The models are illustrated with two surveys on doping use. We conclude with a discussion of the pros and cons of the ever/last year design and its potential for future research. Competing Interests: Declarations. Conflict of interest: The authors have no competing interests to declare that are relevant to the content of this article. (© 2024. The Author(s).)
Databáze:	MEDLINE
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