Daftar Isi: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 9. Nlogit for applied choice analysis 10. Data set up for nlogit 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 20. Frontiers of choice analysis 21. Attribute processing heuristics and preference construction 22. Group decision making