ArticleBehavioural processes2022
An introduction to "discrete choice experiments" for behavior analysts.
Article in Behavioural processes, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
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8 citing papers in PubMed, 1 synthesis or guideline pooled it, 26 citations in OpenAlex.
- Discrete Choice Experiments and Conjoint Analyses in Health Screening Programs for Type 2 Diabetes and Liver Disease: A Scoping Review.Canadian liver journal · 2025Pooled it
- Tobacco control policies that influence Filipino adults who smoke: Results from a discrete choice experiment.Tobacco induced diseases · 2026Article
- Preferences for multi-cancer tests (MCTs) in primary care: discrete choice experiments of general practitioners and the general public in England.British journal of cancer · 2025Article
- Preferences for Mobile App Features to Support People Living With Chronic Heart Diseases: Discrete Choice Study.JMIR mHealth and uHealth · 2025Article
- Inpatient preferences among patients with multiple chronic conditions in China: A discrete choice experiment.BMC primary care · 2025Article
- Discrete choice experiments: a primer for the communication researcher.Frontiers in communication · 2025Article
- Which factors drive the choice of the French-speaking Quebec population towards a COVID-19 vaccination programme: A discrete-choice experiment.Health expectations : an international journal of public participation in health care and health policy · 2024Article
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3 authors at 2 institutions in 1 country.
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Abstract
In this paper, we introduce discrete choice experiments (DCEs) and provide foundational knowledge on the topic. DCEs are one of the most popular methods within econometrics to study the distribution of choices within a population. DCEs are particularly useful when studying the effects of categorical variables on choice. Procedurally, a DCE involves recruiting a large sample of individuals exposed to a set of choice arrays. The factors that are suspected to affect choice are varied systematically across the choice arrays. Most commonly, DCE data are analyzed with a multinomial logit statistical model with a goal of determining the relative utility of each relevant factor. We also discuss DCEs in comparison with behavioral choice models, such as those based on the matching law, and we show an example of a DCE to illustrate how a DCE can be used to understand choice with behavioral, social, and organizational factors.
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