Do randomized-response designs eliminate response biases? An empirical study of non-compliance behavior
Do randomized-response designs eliminate response biases? An empirical study of non-compliance behavior
Out of the toolbox of survey methods for obtaining honest answers to sensitive issues, the method of randomized responses (RR) has proven to be the most effective one. So far, in applications of RR methods it has been assumed that they eliminate response biases. We investigate the validity of this assumption by applying multivariate RR models that allow for different types of response biases. Our data analyses show that RR methods do not eliminate response biases but that they can be modeled in informative ways: accounting for response biases leads to estimates that are at least twice the size of the estimates obtained when response biases are ignored
377-392
Böckenholt, Ulf
580c976b-4040-4cb2-877c-35e042a224df
Barlas, Sema
70946aff-6ec5-4574-bfe1-3e85b35c547b
van der Heijden, Peter G.M.
85157917-3b33-4683-81be-713f987fd612
April 2009
Böckenholt, Ulf
580c976b-4040-4cb2-877c-35e042a224df
Barlas, Sema
70946aff-6ec5-4574-bfe1-3e85b35c547b
van der Heijden, Peter G.M.
85157917-3b33-4683-81be-713f987fd612
Böckenholt, Ulf, Barlas, Sema and van der Heijden, Peter G.M.
(2009)
Do randomized-response designs eliminate response biases? An empirical study of non-compliance behavior.
Journal of Applied Econometrics, 24 (3), .
(doi:10.1002/jae.1052).
Abstract
Out of the toolbox of survey methods for obtaining honest answers to sensitive issues, the method of randomized responses (RR) has proven to be the most effective one. So far, in applications of RR methods it has been assumed that they eliminate response biases. We investigate the validity of this assumption by applying multivariate RR models that allow for different types of response biases. Our data analyses show that RR methods do not eliminate response biases but that they can be modeled in informative ways: accounting for response biases leads to estimates that are at least twice the size of the estimates obtained when response biases are ignored
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Published date: April 2009
Organisations:
Statistical Sciences Research Institute
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Local EPrints ID: 344669
URI: http://eprints.soton.ac.uk/id/eprint/344669
ISSN: 0883-7252
PURE UUID: a6282c0d-4ad8-4d68-ada8-e1e2a8a005b3
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Date deposited: 08 Nov 2012 08:34
Last modified: 23 Feb 2023 03:00
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Author:
Ulf Böckenholt
Author:
Sema Barlas
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