A fully updated second edition of this popular book on choice analysis, showing the latest developments in behavioural theory, econometric estimation, and how to apply all methods using the software NLOGIT. Complete with new topics and case studies, this is a valuable resource for students, researchers, professionals and consultants.
A fully updated second edition of this popular book on choice analysis, showing the latest developments in behavioural theory, econometric estimation, and how to apply all methods using the software NLOGIT. Complete with new topics and case studies, this is a valuable resource for students, researchers, professionals and consultants.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
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Autorenporträt
David A. Hensher is Professor of Management, and Founding Director of the Institute of Transport and Logistics Studies (ITLS) at The University of Sydney Business School.
Inhaltsangabe
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.
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.
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