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Applied Choice Analysis: A Primer
Abstract
Almost without exception, everything human beings undertake involves a choice. In recent years there has been a growing interest in the development and application of quantitative statistical methods to study choices made by individuals with the purpose of gaining a better understanding both of how choices are made and of forecasting future choice responses. In this primer the authors provide an unintimidating introduction to the main techniques of choice analysis and include detail on themes such as data collection and preparation, model estimation and interpretation and the design of choice experiments. A companion website to the book provides practice data sets and software to estimate the main discrete choice models such as multinomial logit, nested logit and mixed logit. This primer will be an invaluable resource to students as well as of immense value to consultants and professionals, researchers and anyone else interested in choice analysis and modelling.
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“We followed recommended guidelines to design and implement the DCE. [7, 8, 11–16]”
From Assessing the American public's preferences for reforms to teen driving licensure systems: a discrete choice experiment (2026) · cites this paper as [14]
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“Key results are presented and interpreted for the MIXL models (Model 3 and Model 4), based on goodness of fit statistics (McFadden pseudo-R-squared, Akaike and Bayesian information criteria).”
From Assessing the American public's preferences for reforms to teen driving licensure systems: a discrete choice experiment (2026) · cites this paper as [14]
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“Here, we use a mixed-logit model (MMNL) which offers advantages to the more often used multinominal logit (MNL) [32,33].”
From Consumer preferences for teledermoscopy screening to detect melanoma early (2016) · cites this paper as [33]
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Metadata
- Authors
- Hensher, D. A., Rose, J. M., & Greene, W. H.
- Affiliations
- The University of Sydney (AU)
- New York University (US)
- Venue
- Cambridge University Press eBooks
- Publisher
- Cambridge University Press
- Published
- 2005-06-02
- OpenAlex
- W3152367353
- Cited by
- 1,823
- References
- 0
- Citations by year
- 2026: 62 · 2025: 87 · 2024: 104 · 2023: 94 · 2022: 104 · 2021: 121 · 2020: 109 · 2019: 127 · 2018: 95 · 2017: 92 · 2016: 105 · 2015: 136 · 2014: 103 · 2013: 95 · 2012: 98
- FWCI
- 34.17
- Type
- book
- Language
- en
- Open access
- closed
- Locations
- Cambridge University Press eBooks (publishedVersion)
- Topics
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Economic and Environmental Valuation
- Social Sciences › Decision Sciences › General Decision Sciences › Decision-Making and Behavioral Economics
- Social Sciences › Transportation › Transportation Planning and Optimization
- Keywords
- discrete choice models, multinomial logistic regression, nested logit model, mixed logit, discrete choice experiment, choice experiment design
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