title: Discrete Choice Experiments: A Guide to Model Specification, Estimation and Software.
abstract: We provide a user guide on the analysis of data (including best-worst and best-best data) generated from discrete-choice experiments (DCEs), comprising a theoretical review of the main choice models followed by practical advice on estimation and post-estimation. We also provide a review of standard software. In providing this guide, we endeavour to not only provide guidance on choice modelling but to do so in a way that provides a 'way in' for researchers to the practicalities of data analysis. We argue that choice of modelling approach depends on the research questions, study design and constraints in terms of quality/quantity of data and that decisions made in relation to analysis of choice data are often interdependent rather than sequential. Given the core theory and estimation of choice models is common across settings, we expect the theoretical and practical content of this paper to be useful to researchers not only within but also beyond health economics.
authors.affiliation: Centre for Health Economics, Monash Business School, Monash University, 75 Innovation Walk, Clayton, VIC, 3800, Australia. Emily.Lancsar@monash.edu.
authors.forename: Emily
authors.initials: E
authors.lastname: Lancsar
authors.affiliation: School of Economics, University of New South Wales, Sydney, NSW, Australia.
authors.forename: Denzil G
authors.initials: DG
authors.lastname: Fiebig
authors.affiliation: Department of Economics, University of Sheffield, Sheffield, UK.
authors.forename: Arne Risa
authors.initials: AR
authors.lastname: Hole
mesh_terms: D002755:Choice Behavior; D006302:Health Services Research; D006801:Humans; D017059:Models, Econometric; D057240:Patient Preference; D012984:Software