Maximising responses to discrete choice experiments: a randomised trial

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dc.contributor.author Coast, J
dc.contributor.author Flynn, TN
dc.contributor.author Salisbury, C
dc.contributor.author Louviere, JJ
dc.contributor.author Peters, T
dc.date.accessioned 2009-12-21T02:36:30Z
dc.date.issued 2006-01
dc.identifier.citation Applied Health Economics and Health Policy, 2006, 5 (4), pp. 249 - 260
dc.identifier.issn 1175-5652
dc.identifier.other C1 en_US
dc.identifier.uri http://hdl.handle.net/10453/5064
dc.description.abstract To identify any differences in response and completion rates across two versions of a questionnaire, in order to determine the trade-off between a potentially higher response rate (from a short questionnaire) and a greater level of information from each respondent (from a long questionnaire). METHODS: This was a randomised trial to determine whether response rates and/or results differ between questionnaires containing different numbers of choices: a short version capable of estimating main effects only and a longer version capable of estimating two-way interactions, provided certain assumptions hold. Best-worst scaling was the form of discrete choice experimentation used. Data were collected by post and analysed in terms of response rates, completion rates and differences in mean utilities. RESULTS: Fifty-three percent of individuals approached agreed to take part. From these, the response to the long questionnaire was 83.2% and the short questionnaire was 85.1% (difference 1.9%, 95% CI -7.3, 11.2; p = 0.68). The two versions of the questionnaire provided similar inferences.
dc.publisher Adis International Ltd
dc.title Maximising responses to discrete choice experiments: a randomised trial
dc.type Journal Article
dc.description.version Published
dc.parent Applied Health Economics and Health Policy
dc.journal.volume 4
dc.journal.volume 5
dc.journal.number 4 en_US
dc.publocation Auckland, New Zealand en_US
dc.identifier.startpage 249 en_US
dc.identifier.endpage 260 en_US
dc.cauo.name BUS.School of Marketing en_US
dc.conference Verified OK en_US
dc.conference IEEE International Conference on Robotics and Automation (ICRA)
dc.for 140208 Health Economics
dc.personcode 020132
dc.personcode 102815
dc.percentage 100 en_US
dc.classification.name Health Economics en_US
dc.classification.type FOR-08 en_US
dc.date.activity 2006-05-15
dc.location.activity Orlando, FL
dc.description.keywords DCE; rationality; consumer theory; preference elicitation en_US
dc.description.keywords Science & Technology
dc.description.keywords Technology
dc.description.keywords Automation & Control Systems
dc.description.keywords Computer Science, Artificial Intelligence
dc.description.keywords Engineering, Mechanical
dc.description.keywords Robotics
dc.description.keywords Computer Science
dc.description.keywords Engineering
dc.description.keywords SIMULTANEOUS LOCALIZATION
dc.description.keywords DCE
dc.description.keywords rationality
dc.description.keywords consumer theory
dc.description.keywords preference elicitation
dc.description.keywords DCE
dc.description.keywords DCE
dc.description.keywords rationality
dc.description.keywords rationality
dc.description.keywords consumer theory
dc.description.keywords consumer theory
dc.description.keywords preference elicitation
dc.description.keywords preference elicitation
dc.description.keywords DCE
dc.description.keywords rationality
dc.description.keywords consumer theory
dc.description.keywords preference elicitation
pubs.embargo.period Not known
pubs.organisational-group /University of Technology Sydney
pubs.organisational-group /University of Technology Sydney/Faculty of Business
pubs.organisational-group /University of Technology Sydney/Strength - Study of Choice
utslib.copyright.status Closed Access
utslib.copyright.date 2015-04-15 12:17:09.805752+10


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