The multidimensional randomized response design: estimating different aspects of the same sensitive behavior
The multidimensional randomized response design: estimating different aspects of the same sensitive behavior
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 (i i) evaluate the goodness-of-fit of the model, and (i i i) 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
randomized response, power, efficiency, response bias
1-10
Cruyff, M.
87113ca0-c784-493a-b96e-5ad4a9e16465
Bockenholt, U.
ab134de4-5066-4e1d-923b-3ff42cad840a
van der Heijden, P.G.M.
85157917-3b33-4683-81be-713f987fd612
Cruyff, M.
87113ca0-c784-493a-b96e-5ad4a9e16465
Bockenholt, U.
ab134de4-5066-4e1d-923b-3ff42cad840a
van der Heijden, P.G.M.
85157917-3b33-4683-81be-713f987fd612
Cruyff, M., Bockenholt, U. and van der Heijden, P.G.M.
(2015)
The multidimensional randomized response design: estimating different aspects of the same sensitive behavior.
Behavior Research Methods, .
(doi:10.3758/s13428-015-0583-2).
(PMID:25877782)
Abstract
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 (i i) evaluate the goodness-of-fit of the model, and (i i i) 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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e-pub ahead of print date: 16 April 2015
Keywords:
randomized response, power, efficiency, response bias
Organisations:
Statistical Sciences Research Institute
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Local EPrints ID: 381218
URI: http://eprints.soton.ac.uk/id/eprint/381218
ISSN: 1554-351X
PURE UUID: b243c59e-6a97-4ce1-86bf-837f8c455f32
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Date deposited: 25 Sep 2015 13:55
Last modified: 15 Mar 2024 03:46
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Author:
M. Cruyff
Author:
U. Bockenholt
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