Applied Choice Analysis (Paperback, 2 Revised edition)

Preface; Part I. Getting Started: 1. In the beginning; 2. Choosing; 3. Choice and utility; 4. Families of discrete choice models; 5. Estimating discrete choice models; 6. Experimental design and choice experiments; 7. Statistical inference; 8. Other matters that analysts often inquire about; Part II. Software and Data: 9. Nlogit for applied choice analysis; 10. Data set up for Nlogit; Part III. The Suite of Choice Models: 11. Getting started modeling: the workhorse - multinominal logit; 12. Handling unlabeled discrete choice data; 13. Getting more from your model; 14. Nested logit estimation; 15. Mixed logit estimation; 16. Latent class models; 17. Binary choice models; 18. Ordered choices; 19. Combining sources of data; Part IV. Advanced Topics: 20. Frontiers of choice analysis; 21. Attribute processing, heuristics, and preference construction; 22. Group decision making; Select glossary; References; Index.