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In recent years, there has been growing interest in the development and application of quantitative statistical methods to study choices made by individuals. This primer provides an introduction to the main techniques of choice analysis and also includes details on data collection and preparation, model estimation and interpretation and the design of choice experiments. A companion website offers practice data sets and software to apply modeling and data skills presented in the book.Read more
- Was the first book to help individuals new to the theory and practice of choice analysis
- Data and statistical software available to apply all the modeling and data skills presented in the book
- The book and software is ready made for undergraduate and post graduate courses as well as short courses and is portable throughout the world
Reviews & endorsements
"...this book should be required reading for anybody who carries out (or hopes to carry out) serious choice analysis. I cannot think of any choice study, including most of the ones in which I have participated, that could not be improved by following the practical advice given in thsi book. After years of teaching some of this material to economics graduate students, I have a mental list of "stupid" mistakes that most of them will make. This book not only lists almost all of these mistakes, it carefully explains why they are mistakes and shows how to avoid them." - Journal of the American Statistical Association David Brownstone, University of California, Irvine
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- Date Published: August 2005
- format: Paperback
- isbn: 9780521605779
- length: 744 pages
- dimensions: 244 x 170 x 38 mm
- weight: 1.17kg
- contains: 108 tables
- availability: Available
Table of Contents
1. In the beginning
2. Basic notations of statistics
4. Paradigms of choice data
5. Processes in setting up stated choice experiments
6. Choices in data collection
7. Nlogit for applied choice analysis: a primer
8. Handling choice data
9. Case study: model choice data
10. Getting started modelling: the workhorse - MNL
11. Getting more from your model
12. Practical issues in the application of choice models
13. Allowing for similarity of alternatives
14. Nested logit estimation
15. The mixed logit model
16. Mixed logit estimation
Nlogit terms and commands
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