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The Construction of Optimal Stated Choice Experiments: Theory and Methods

ISBN: 978-0-470-05332-4
344 pages
July 2007
The Construction of Optimal Stated Choice Experiments: Theory and Methods (0470053321) cover image
The most comprehensive and applied discussion of stated choice experiment constructions available

The Construction of Optimal Stated Choice Experiments provides an accessible introduction to the construction methods needed to create the best possible designs for use in modeling decision-making. Many aspects of the design of a generic stated choice experiment are independent of its area of application, and until now there has been no single book describing these constructions. This book begins with a brief description of the various areas where stated choice experiments are applicable, including marketing and health economics, transportation, environmental resource economics, and public welfare analysis. The authors focus on recent research results on the construction of optimal and near-optimal choice experiments and conclude with guidelines and insight on how to properly implement these results. Features of the book include:

  • Construction of generic stated choice experiments for the estimation of main effects only, as well as experiments for the estimation of main effects plus two-factor interactions
  • Constructions for choice sets of any size and for attributes with any number of levels

  • A discussion of designs that contain a none option or a common base option

  • Practical techniques for the implementation of the constructions

  • Class-tested material that presents theoretical discussion of optimal design

  • Complete and extensive references to the mathematical and statistical literature for the constructions

  • Exercise sets in most chapters, which reinforce the understanding of the presented material

The Construction of Optimal Stated Choice Experiments serves as an invaluable reference guide for applied statisticians and practitioners in the areas of marketing, health economics, transport, and environmental evaluation. It is also ideal as a supplemental text for courses in the design of experiments, decision support systems, and choice models. A companion web site is available for readers to access web-based software that can be used to implement the constructions described in the book.

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List of Tables.

Preface.

Chapter 1. Typical Stated Choice Experiments.

Chapter 2. Factorial Designs.

Chapter 3. The MNL Model and Comparing Designs.

Chapter 4. Paired Comparison Designs for Binary Attributes.

Chapter 5. Larger Choice Set Sizes for Binary Attributes.

Chapter 6. Designs for Asymmetric Attributes.

Chapter 7. Various Topics.

Chapter 8. Practical Techniques For Constructing Choice Experiments.

Bibliography.

Index.

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Deborah J. Street, PhD, is Professor of Statistics at the University of Technology, Sydney in Australia. She has over twenty years of academic experience in the construction of designed experiments and has published over 100 articles on the subject.

Leonie Burgess, PhD, is Senior Research Fellow in Mathematical Sciences at the University of Technology, Sydney in Australia. Her research interests include the design and computer-based construction of experiments, and she has published many research papers on the design and construction of optimal choice experiments.

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"Individuals involved in researching, learning about, or using SCE's are most likely to find this book useful." (Biometrics, September 2008)

"Individuals involved in researching, learning about, or using SCE's are most likely to find this book useful." (Biometrics, Sept 2008)

"This book provides an excellent treatment of structure of D-optimal designs for choice experiments. I enjoyed reading it.." (Journal of the American Statistical Association, Sept 2008)

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"Individuals involved in researching, learning about, or using SCE's are most likely to find this book useful." (Biometrics, Sept 2008)

"This book provides an excellent treatment of structure of D-optimal designs for choice experiments. I enjoyed reading it.." (Journal of the American Statistical Association, Sept 2008)

See More
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