Overview
Binary (proportion/percentage) outcomes are common in medical and scientific research and cannot be validly analysed using basic linear regression analysis. It is important to understand how to analyse these types of outcomes appropriately to ensure useful and valid conclusions are drawn from data.
The logistic regression course covers the following key topics:
- Odds ratios as a means of comparing binary outcomes between two groups
- How logistic regression allows for other factors within this comparison
- The basics of logistic regression
- Model selection and goodness-of-fit with applied examples
Concessions
A 50% discount is available for UCL staff, students, alumni. If you're eligible for a discount, email ich.statscou@ucl.ac.uk before booking to be sent the discount code.
The course is available for free to those associated with the Institute of Child Health or Great Ormond Street Hospital, and UCL doctoral students. Please also email ich.statscou@ucl.ac.uk to gain a booking code.
Learning outcomes
By the end of the course you should be able to:
- identify contexts in which logistic regression is appropriate
- discuss the theoretical basis of logistic regression
- interpret output produced by SPSS when fitting logistic regression models
- use the goodness-of-fit measures to choose between competing models
- evaluate model fit
- interpret and critically appraise results published in papers using logistic regression
Find out about other statistics courses
CASC's stats courses are suitable for anyone requiring an understanding of research methodology and statistical analyses. The courses allow non-statisticians to interpret published research and/or undertake their own research studies.
Find out more about CASC's full range of statistics courses.
