This course gives a practical, non-mathematical introduction to the use of logistic regression in the analysis of categorical outcomes.

Logistic regression is a widely used technique for the analysis of categorical data, offering increased flexibility compard to the traditional analysis of crosstables. A binary outcome can be predicted using one or more categorical variables, continuous variables or combinations thereof.

The course starts with an online self-study through a starter's package, followed by two in-class lectures. Participants are expected to complete the starter's package by the first in-class lecture. The software package SPSS will be used in the exercises.

For this course, we offer the possibility to take an exam. For the PhD students in the faculties IOB and Applied Economics, this is a requirement to obtain a credits for these courses, but people from other faculties are allowed as well.
If you are interested in taking the exam, check the wants-to-take-exam-box in the registration form. Participating in the exam costs 10€, which is deduced automatically from your educational credit.

Course contents

  • Starter's package (to be completed by the first lecture)
    • Introduction to categorical variables
    • The odds ratio
    • Stratified analysis
  • Lecture 1 (full day)
    • Q&A and feedback on the starter's package
    • Simple logistic regression
    • Multiple logistic regression
  • Lecture 2 (half day)
    • Prediction using logistic regression
    • ROC curves
    • Checking the validity of a model

Target audience / prerequisites

Pre- and postdoctoral students from all research fields. No specific mathematical knowledge is required.

Participants should be familiar with linear regression and the use of SPSS, at the level of StatUa's Basic Principles of Statistics course.



PhD student UAntwerpen : € 50 

UA-affiliated : € 90

Academic non-UA : € 160

Publicand non-profit sector : € 250

Private sector : € 500




Time and place

The next course will take place in May 28-29-30, 2024.