| Autor: |
Cruyff MJ; Department of Methodology & Statistics, Utrecht University, Padualaan 14, 3584, CH Utrecht, The Netherlands. m.cruyff@uu.nl., Böckenholt U; Kellogg School of Management, Northwestern University, Evanston, IL, USA., van der Heijden PG; Department of Methodology & Statistics, Utrecht University, Padualaan 14, 3584, CH Utrecht, The Netherlands.; S3RI, University of Southampton, Southampton, Great Britain. |
| Abstrakt: |
The conventional randomized response design is unidimensional in the sense that it measures a single dimension of a sensitive attribute, like its prevalence, frequency, magnitude, or duration. This paper introduces a multidimensional design characterized by categorical questions that each measure a different aspect of the same sensitive attribute. The benefits of the multidimensional design are (i) a substantial gain in power and efficiency, and the potential to (ii) evaluate the goodness-of-fit of the model, and (iii) test hypotheses about evasive response biases in case of a misfit. The method is illustrated for a two-dimensional design measuring both the prevalence and the magnitude of social security fraud. |
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