Applied Choice Analysis: A Primer

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.

Table of Contents:
Preface; 1. In the beginning; 2. Basic notations of statistics; 3. Choosing; 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; References; Index.

About the Author :
David A. Hensher is Director of the Institute of Transport Studies and Professor of Management in the Faculty of Economics and Business at the University of Sydney. John M. Rose is a Lecturer at the Institute of Transport Studies at the University of Sydney. William H. Greene is Professor of Economics and Entertainment and Media Faculty Fellow in the Department of Economics at the Stern School of Business, New York University.

Review :
'I cannot imagine a better introduction to choice modeling. The authors manage to bring a vivid, storytelling voice to this complex topic, with language that has personality and rhythm. The various interrelated concepts and procedures that constitute choice modeling come across as simple and straightforward. An amazing feat. The ins-and-outs of a computer code are also taught along with the statistical methods. This integration of computer language within the text is unusual and highly valuable, giving readers all the steps that are needed to implement the methods on their own data.' Kenneth Train, Adjunct Professor, University of California, Berkeley 'With all knowledge, the fundamental concepts constitute the most important part of learning. Hensher et al. have taken this to heart and done a superb job here in explaining the trickiest of discrete choice survey and analysis concepts in a simple, elegant, and intuitive fashion. This book, written by leading authorities in the discrete choice field, is required reading not only for beginners, but also for those experienced researchers who would like to clarify basic concepts. It is a much-needed and welcome addition to a field that is seeing a literal revolution in the analyst's ability to incorporate and estimate realistic behavioral structures. The book holds the hands of readers and walks them through the new developments in the field. Let it not be said any more that the recent advances in discrete choice analysis are beyond the reach of all but the nerdiest of researchers!' Chandra Bhat, University of Texas, Austin