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Logistic Regression

Date:

08/12/2017

Organised by:

University of Manchester

Presenter:

Maria Pampaka

Level:

Entry (no or almost no prior knowledge)

Contact:

Anthony Bacon, 0161 2751980, cmist-courses@manchester.ac.uk

Map:

View in Google Maps  (M13 9PL)

Venue:

Humanities Bridgeford Street, University of Manchester. Oxford Road, Greater Manchester

Description:

Outline

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.

Prerequisites

Participants should have:

  • a basic familiarity with SPSS;
  • 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. 

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.

Cost:

£195 (£140 for those from educational, government and charitable institutions).

Website and registration:

Region:

North West

Keywords:

Survey Research, Qualitative longitudinal research (QLR), Instrumental variables, Analysis of existing survey data, Mixed Methods, Qualitative sampling, Survey and Questionnaire Design, Quality in Quantitative Research, Quantitative Data Handling and Data Analysis, Correlation, Levels of measurement, Regression Methods, Linear regression, Logistic regression, SPSS, Logistic regression

Related publications and presentations:

Survey Research
Qualitative longitudinal research (QLR)
Instrumental variables
Analysis of existing survey data
Mixed Methods
Qualitative sampling
Survey and Questionnaire Design
Quality in Quantitative Research
Quantitative Data Handling and Data Analysis
Correlation
Levels of measurement
Regression Methods
Linear regression
Logistic regression
SPSS

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