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Pouring water into wine: Revisiting the advantages of the crosswise model for asking sensitive questions
[journal article]
Abstract The Crosswise Model (CM) has been proposed as a method to reduce effects of social
desirability in sensitive questions. In contrast with former variants of Randomized Response
Techniques (RRTs), the crosswise model neither offers a self-protective response strategy, nor
does it require a random d... view more
The Crosswise Model (CM) has been proposed as a method to reduce effects of social
desirability in sensitive questions. In contrast with former variants of Randomized Response
Techniques (RRTs), the crosswise model neither offers a self-protective response strategy, nor
does it require a random device. For these reasons, the crosswise model has received a lot of
positive attention in the scientific community. However, previous validation studies have mostly
analysed negatively connoted behaviour and thus draw on the principle of “more is better”.
Higher prevalence rates of socially undesirable behaviour in the crosswise model cannot be
attributed unambiguously to a reduction in social desirability bias, since random ticking
resulting from respondent confusion about the question format cannot be ruled out as an
alternative explanation. Unlike most research on crosswise models and randomized response
techniques, we conduct an experiment in a general population survey that does not assess
negatively connoted but socially desirable behaviour (namely, whether respondents had
donated blood within the last twelve months). This design allows us to empirically disentangle
the reduction of social desirability bias from random responses. We find signifcantly higher
prevalence rates in the crosswise condition than in the direct question. What is more, we
could not identify any subgroup of respondents, in which the CM successfully reduced social
desirability bias. These results cast doubts on the validity of cosswise models. They suggest
that a considerable number of respondents do not comply with the intended procedure.... view less
Keywords
random sample; model; regression analysis; anonymity; validity; social desirability; response behavior; survey research; data capture
Classification
Methods and Techniques of Data Collection and Data Analysis, Statistical Methods, Computer Methods
Free Keywords
crosswise model; randomised response techniques; sensitive questions; social desirability
Document language
English
Publication Year
2019
Page/Pages
p. 1-16
Journal
Survey Methods: Insights from the Field (2019)
ISSN
2296-4754
Status
Published Version; peer reviewed