B004630 - STATISTICAL MODELS (ADVANCED)

Italian

The course covers the theory and application of generalized linear models. In particular: linear regression model and analysis of variance; theory of generalized linear models; models for categorical response variables, models for counts, multilevel models. The models will be used for the analysis of real data using the software Stata, with particular attention to the choice of the model and interpretation of the results.

- Dobson A.J., Barnett A.G. (2008). An introduction to Generalized Linear Models, 3rd Edition, CRC Press.
- JH Stock, MW Watson (2006) - Introduction to Econometrics (Second Edition), Addison Wesley. Versione italiana: Introduzione all'Econometria (2009, Seconda edizione), ed. Pearson Italia.

Knowledge of the properties and potentialities of the main statistical models. Ability to select the most appropriate model depending on the research aims and the available data. Ability to estimate the selected model, to evaluate the model adequacy and to interpret the results. Ability to write a short report on the analysis.

Basic knowledge of probability calculus and classical statistical inference.
Compulsory prerequisite exam: "Statistical Inference".

Classroom lessons and lab activities.

paper examination, computer exercise, and oral examination

1. The linear regression model: a review with applications (SW 2005: ch. 4,5 e 6)
1.1. Simple linear regression
1.2. Multiple Linear regression
1.3. Non linear functions
1.4. Interactions
2 .Theory of generalised linear models (DB 2008: ch. 1-5)
2.1. exponential family
2.2. generalised linear models
2.3. estimation
2.4. inference
3. Linear models and analysis of variance (DB 2008: ch. 6)
4. Models for categorical responses (DB 2008: ch. 7-8)
4.1. Binary responses and logistic regression
4.2. Ordinal and nominal responses
5. Models for counts and Poisson regression (DB 2008: ch. 9)
6. Multilevel models