1. Introduction

Part I. Behavioral Models:
2. Properties
3. Logit
4. GEV
5. Probit
6. Mixed logit
7. Variations on a theme

Part II. Estimation:
8. Numerical maximization
9. Drawing from densities
10. Simulation-assisted estimation
11. Individual-level parameters
12. Bayesian procedures
13. Endogeneity
14. EM algorithms