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Applied Choice Analysis: A Primer

Hensher, David A., Rose, John M., Greene, William H.·2005·Cambridge University Press eBooks

DOI 10.1017/cbo9780511610356

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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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Authors: Hensher, D. A., Rose, J. M., & Greene, W. H.
Affiliations: The University of Sydney (AU)
New York University (US)
ORCID: Hensher, David A.
Rose, John M.
Greene, William H.
Venue: Cambridge University Press eBooks
Publisher: Cambridge University Press
Published: 2005-06-02
DOI: 10.1017/cbo9780511610356
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
Licence: www.cambridge.org/core/terms (unspecified, 2652 d)
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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Applied Choice Analysis: A Primer

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