Applied Regression Methods
Tipo di corso: Corso per dottorandi
Valore in crediti ECTS: 1.5
Registrazione online/ Online Registration: http://www.phdsubscription.lu.usi.ch
06 March 2012: 13:30-17:00, Aula, 402
08 March 2012: 13:30-17:00, Aula, 402
20 March 2012: 13:30-17:00, Aula, 402
22 March 2012: 13:30-17:00, Aula 354
This course introduces a wide range of modern regression methods. This course is designed to provide students with an overview of basic and advanced topics in regression analysis. Students will develop an understanding of the purpose, rationale, and uses of the various regression analyses with a focus on application and interpretation rather than derivation. The course will extend the ability to read scientific literature and critically evaluate study designs and methods of data analysis. Emphasis is on modeling driven by actual data from studies in from the social sciences. Primary topics include multiple linear regression, logistic regression, Poisson regression and time series regression. A fundamental goal is to learn what approach to use among the linear and nonlinear models, and how to determine if model fit is adequate. Regression techniques will be used in SPSS and R.
Upon completion of the course, students will be able to:
- Select appropriate methods for specific data, especially in determining whether a linear or a nonlinear approach to regression is appropriate
- Understand the appropriate procedures for performing regression analysis in SPSS or R.
- Test and interpret linear models for continuous outcome data (normal linear model).
- Test and interpret models for categorical outcome data (logistic and Poisson regression).
- Test and interpret models for time series data.
- Communicate clearly the purposes and results of statistical analysis, both orally and in writing.