Logistic Regression
Date:
18/01/2019
Organised by:
The University of Manchester
Presenter:
Dr Maria Pampaka
Level:
Entry (no or almost no prior knowledge)
Contact:
CMI Short Courses
cmi-shortcourses@manchester.ac.uk
0161 2751980
Description:
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.
You will also learn how to fit a logistic regression model, and how to interpret the results.
The course uses SPSS as the platform for analysis.
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.
Cost:
£195 (£140 for those from educational, government and charitable institutions)
Website and registration:
https://www.cmist.manchester.ac.uk/study/short/list/
Region:
North West
Keywords:
Regression discontinuity, Regression Methods, Linear regression, Categorical data analysis, Latent Variable Models, SPSS
Related publications and presentations:
Regression discontinuity
Regression Methods
Linear regression
Categorical data analysis
Latent Variable Models
SPSS