1. Introduction
Why probability models?
Why interpretation?
2. Generalized linear models and the interpretation of parameters
Generalized linear models
Interpretation of parameter estimates
3. Binary logit and probit models
Logit models
Interpretation of logit models
Probit models
Interpretation of probit models
Logit or probit models?
4. Sequential logit and probit models
The model
Interpretation of sequential logit and probit models
5. Ordinal logit and probit models
The model
Interpretation of ordinal logit and probit models
6. Multinomial logit models
The model
Interpretation of multinomial logit models
7. Conditional logit models
The model
Interpretation of conditional logit models
8. Poisson regression models
The model
Interpretation of poisson regression models
9. Conclusion.