Discrete Choice Experiments: A Guide to Model Specification, Estimation and Software
2017
This is 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. Authors also provide a review of standard software.
Authors 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, they expect the theoretical and practical content of this paper to be useful to researchers not only within but also beyond health economics.
Discrete Choice Experiments: A Guide to Model Specification, Estimation and Software
Source:
Lancsar E, Fiebig DG, Hole AR. Discrete Choice Experiments: A Guide to Model Specification, Estimation and Software. PharmacoEconomics 2017; 35 (7): 697-716. https://doi.org/10.1007/s40273-017-0506-4