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B004651 - MODELLI DEMOGRAFICI
Principali informazioni
Lingua Insegnamento
Contenuto del corso
Libri di testo consigliati
Obiettivi Formativi
Prerequisiti
Metodi Didattici
Modalità di verifica apprendimento
Programma del corso
Anno Accademico 2014-15
Anno di corso
Primo Anno - Secondo Semestre
Dipartimento di Afferenza
Statistica, Informatica, Applicazioni "G. Parenti" (DiSIA)
Tipo insegnamento
Attività formativa monodisciplinare
Settore Scientifico disciplinare
SECS-S/04 - DEMOGRAFIA
Crediti Formativi
9
Ore Didattica
72
Periodo didattico
02/03/2015 ⇒ 05/06/2015
Frequenza Obbligatoria
No
Tipo Valutazione
Voto Finale
Contenuto del corso
mostra
Programma del corso
mostra
Docenza
Lingua Insegnamento
INGLESE
Contenuto del corso
This course is an introduction to theory and applications of event-history analysis (also known as survival analysis, hazard regression, intensity regression, or duration data analysis). Duration data is commonly used to address many research questions in demography, social sciences, and epidemiology.
Libri di testo consigliati (Cerca nel catalogo della biblioteca)
Hans-Peter Blossfeld, Katrin Golch, Gotz Rohwer (2007). Event History Analysis with Stata. Taylor & Francis Group.
Obiettivi Formativi
This course covers univariate and multivariate (regression) methods for analysis of duration (event-history) data, including their recent developments. Students also learn data management skills that are specific to conducting event-history analysis in Stata. Throughout the course students will apply event-history techniques to own research projects.
Prerequisiti
STATISTICAL INFERENCE
Metodi Didattici
Students also learn data management skills through specific assignments to be solved using Stata. Throughout the course students will apply event-history techniques to specific mini-projects agreed with the teacher.
Modalità di verifica apprendimento
Written exam + Assignments + Mini-project
Programma del corso
1. Review of basic demography: definitions, pop structures, lexis grid, rates and probabilities; life-table analysis; population projections.
2. Conceptual framework of Even History Analysis (EHA): from macro to micro
3. Basic tools of EHA: longitudinal data and life-table estimator; Kaplan-Maier survival curves; Episode splitting.
4. Sequence Analysis.
5. EHA modelling: basic modeling (exponential model, piece-wise constant exponential model), interactions.
6. Discrete- and continuous-time models.
7. Parametric models.
8. Semi-parametric Cox model.
9. Competing risk models.
10. Interpretation and causation in EHA.
11. Advances in EHA: unobserved heterogeneity, simultaneous models.
12. Back to Macro
13. STATA: Several lab sessions
2. Conceptual framework of Even History Analysis (EHA): from macro to micro
3. Basic tools of EHA: longitudinal data and life-table estimator; Kaplan-Maier survival curves; Episode splitting.
4. Sequence Analysis.
5. EHA modelling: basic modeling (exponential model, piece-wise constant exponential model), interactions.
6. Discrete- and continuous-time models.
7. Parametric models.
8. Semi-parametric Cox model.
9. Competing risk models.
10. Interpretation and causation in EHA.
11. Advances in EHA: unobserved heterogeneity, simultaneous models.
12. Back to Macro
13. STATA: Several lab sessions