Repeated cross-sectional randomized response data
Repeated cross-sectional randomized response data
Randomized response (RR) is an interview technique that can be used to protect the privacy of respondents if sensitive questions are posed. This paper explains how to measure change in time if a binary RR question is posed at several time points. In cross-sectional research settings, new insights often gradually emerge. In our setting, a switch to another RR procedure necessitates the development of a trend model that estimates the effect of the covariate time if the dependent variable is measured by different RR designs. We also demonstrate that it is possible to deal with self-protective responses, thus accommodating our trend model with the latest developments in RR data analysis.
linear trend, longitudinal data, misclassification, randomized response, repeated cross-sections, self-protective responses
145-152
Frank, L.E.
27f1b61a-3f36-40a1-93d1-3a373de7161e
van den Hout, A.
0292f270-5479-4af9-a5af-990af7865d43
van der Heijden, P.G.M.
85157917-3b33-4683-81be-713f987fd612
2009
Frank, L.E.
27f1b61a-3f36-40a1-93d1-3a373de7161e
van den Hout, A.
0292f270-5479-4af9-a5af-990af7865d43
van der Heijden, P.G.M.
85157917-3b33-4683-81be-713f987fd612
Frank, L.E., van den Hout, A. and van der Heijden, P.G.M.
(2009)
Repeated cross-sectional randomized response data.
Methodology: European Journal of Research Methods for the Behavioral and Social Sciences, 5 (4), .
(doi:10.1027/1614-2241.5.4.145).
Abstract
Randomized response (RR) is an interview technique that can be used to protect the privacy of respondents if sensitive questions are posed. This paper explains how to measure change in time if a binary RR question is posed at several time points. In cross-sectional research settings, new insights often gradually emerge. In our setting, a switch to another RR procedure necessitates the development of a trend model that estimates the effect of the covariate time if the dependent variable is measured by different RR designs. We also demonstrate that it is possible to deal with self-protective responses, thus accommodating our trend model with the latest developments in RR data analysis.
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Published date: 2009
Keywords:
linear trend, longitudinal data, misclassification, randomized response, repeated cross-sections, self-protective responses
Organisations:
Statistical Sciences Research Institute
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Local EPrints ID: 344672
URI: http://eprints.soton.ac.uk/id/eprint/344672
ISSN: 1614-1881
PURE UUID: 51be9a02-888a-418f-b369-c00651afca7b
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Date deposited: 26 Oct 2012 13:30
Last modified: 15 Mar 2024 03:46
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Author:
L.E. Frank
Author:
A. van den Hout
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