Aspects of Statistical Modelling
Dates: 03/06/2009
Duration: 1 day (10am — 4:30pm)
Level: Intermediate
Course Fee: £175 (£125 for those from educational institutions)
CCSR offer 5 free places to research staff and students within the Faculty of Humanities.
Course Leader:
Dr Nikos Tzavidis
Course Requirements: Participants should have a basic familiarity with SPSS - which can be met through the day course: Introduction to SPSS. Also familiarity with the basic regression model is assumed.
Course Summary
This one-day course will cover the following topics: Deciding which type of model is appropriate given the research question and the available data. The course will mainly emphasize on models for categorical data. Topics include: Binary logistic regression; ordinal logistic regression and multinomial logistic regression, model fitting, model selection and the use of likelihood ratio tests, interpreting model coefficients, odds ratios and the output from statistical software. Practical examples will be discussed. An SPSS computer workshop on how to implement different models for categorical data is delivered in the last session.
Course Objectives
To offer participants an introduction to the skills needed for selecting which type of model is appropriate given the research question and the available data and provide a very solid introduction to categorical data analysis.
Participants will
- be introduced to different models for categorical data analysis;
- gain an understanding on what types of categorical data are appropriate for each model;
- gain an understanding of how to perform model selection;
- learn to interpret the results from statistical analysis in a non-technical language;
- gain knowledge on how to use mainstream statistical software for fitting the models that will be presented during the course
Target Audience
The course is designed for users of survey data and assumes knowledge of the basic regression model. It would be particularly appropriate for those who may anticipate working with a survey dataset analyzing categorical data. The course provides a very good basis for using popular categorical data analysis techniques.
Preliminary Reading
- Agresti, A. (1990) ‘Categorical Data Analysis’. John Wiley.
- Agresti, A. (1996) ‘An introduction to Categorical Data Analysis’, John Wiley.
- Dobson, A. (2001) ‘Introduction to Generalized Linear Models, Second Edition’ Chapman and Hall.
- McCullagh, P. and Nelder, J. (1989) ‘Generalised linear models (second edition). Chapman and Hall.
- Plewis, I. (1997) ‘Statistics in Education’. Edward Arnold