Logistic Regression
Dates: 26th April 2012
Duration: 1 day (10am — 4:30pm)
Level: Intermediate
Course Fee: £175 (£125 for those from educational institutions)
CCSR offers 5 free places to research staff and students within the Faculty of Humanities at the University of Manchester and the North West Doctoral Training Centre.
Course Leader: Dr Maria Pampaka
Course Requirements: Participants should have a basic familiarity with SPSS. They should also have an understanding of basic data analytical techniques and concepts such as cross tabulations, graphing, variance, significance testing and correlation. An understanding of linear regression would be helpful but not essential.
Course Summary
This course examines the fitting of models to predict a binary response variable from a mixture of binary and interval explanatory variables. The approach is illustrated using examples from a social science perspective, including cases where logistic regression models are used as a means of analysing tabular data where one of the dimensions of the table is a two-category outcome variable. The participant will also learn how to fit a logistic regression model, and how to interpret the results.
Course Objectives
At the end of the course participants should be able to:
- Understand the concepts of odds and odds ratios.
- Generate odds for a given contingency tables.
- Understand the basic theory behind binary logistic regression.
- Run and interpret a logistic regression model.
- Interpret Log Likelihoods to evaluate models.
- Choose between different models.
Target Audience
The course is designed for users of survey data with some experience of data analysis, who are comfortable using SPSS and who want to expand their understanding of more sophisticated techniques.
Preliminary Reading
- Field, A. (2010) Discovering statistics using SPSS for Windows: London: SAGE Publications. Chapter 6.