Introduction to Linear and Logistic Regression Models
Linear and logistic regression models are essential tools for quantifying the relationship between outcomes and exposures. Understanding the mathematics behind these models and being able to apply them allows students to comprehend the results presented in research papers and interrogate their own data. These models also form the building blocks for more advanced statistical techniques taught in other short courses offered by Bristol Medical School. The tutors of this course have extensive experience teaching applied statistics to a wide range of healthcare researchers, both clinical and non-clinical, using real-world data in demonstrations.
| Dates | 4 - 8 March 2024 |
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| Fee | £1,100 |
| Format | Online |
| Audience | Open to all applicants (prerequisites apply) |
Course profile
This course aims to provide an understanding of the statistical principles behind, and the practical application of, univariable and multivariable linear and logistic regression in medical, epidemiological and health services research.
Please click on the sections below for more information.
Structure
This 5-day course will be online and consist of a mix of live and pre-recorded sessions and practical work. Over the five days there will be approximately 14 hours of lectures and 15 hours of practicals.
Intended Learning Objectives
By the end of the course participants should:
- have a thorough conceptual understanding of linear and logistic regression;
- appreciate the common threads running through these methods, including stratified analysis, different options for handling explanatory variables, and concepts such as confounding and interaction;
- have a working knowledge of the Stata or R commands to run these models, and a thorough understanding of the output generated from such a package; and
- know the basis on which analytical strategy and model choice is made, and how the results should be interpreted.
Target audience
The course is intended for people analysing data from medical, epidemiological, and health services research, who have used simple methods such as t-tests and chi-square tests, and who now wish to use multivariable methods to control confounding, accommodate interaction, and increase statistical power.
Outline
This course will cover:
1. revision of basic methods in a statistical modelling framework;
2. terminology in regression modelling;
3. indicator variables to incorporate categorical explanatory variables;
4. univariable and multivariable regression;
5. common features of linear and logistic regression models;
6. interpretation of model coefficients as differences in means or odds ratios;
7. adjustment for confounding and exploring effect modification (interaction) in multivariable regression;
8. comparing models with Wald tests and likelihood ratio tests;
9. model assumptions; and
10. analytical strategies.
Teaching staff
This course is taught by a team of experienced statisticians from Population Health Sciences who have taught on this and other short courses at Bristol Medical School.
Prerequisites
To make sure the course is suitable for you and you will benefit from attending, please ensure you meet the following prerequisites before booking:
| Knowledge | You should have knowledge of statistical methods and their implementation in Stata of at least the level achieved in the Introduction to Statistics short course. |
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| Software |
You must have Stata (version 15 or higher)* installed in advance of the course. *Internal University of Bristol participants are given access to Stata. Go to Stata Installation Instructions (internal only) for help setting it up before the start of the course. External participants are responsible for providing their own access to Stata, however if you are an employee of a university or another institution you may be able to get a short term free Evaluate license. If you are a student, Stata offer a short term free Student licence (one week). |
| Recommendation | You may find it helpful to have access to two screens - or ability to print materials in advance - in order to run analyses in Stata while having course materials open. This is not essential, however. |
Bookings
Before booking this course, please make sure you read the information provided above about the target audience and prerequisites. It is important that you have access to the relevant IT resources needed for the course and meet the knowledge prerequisites to ensure you can get the most from the course.
Bookings are taken via our online booking system, for which you must register an account. To check if you are eligible for free or discounted courses please see our fees and voucher packs page. All bookings are subject to our terms & conditions, which can be read in full here.
For help and support with booking a course refer to our booking information page, FAQs or feel free to contact us directly. For available payment options please see: How to pay your short course fees.
Course materials
Participants are granted access to our virtual learning platform (Blackboard) 1 to 2 weeks in advance of the course. This allows time for any pre-course work to be completed and to familiarise with the platform.
To gain the most from the course, we recommend that you attend in full and participate in all interactive components. We endeavour to record all live lecture sessions and upload these to the online learning environment within 24 hours. This allows course participants to review these sessions at leisure and revisit them multiple times. Please note that we do not record breakout sessions.
All course participants retain access to the online learning materials and recordings for 3 months after the course.
University of Bristol staff and postgraduate students who do not wish to attend the full course may instead register for access to the 'Materials & Recordings' version of this course: Further information and bookings.
Testimonials
100% of attendees recommend this course*.
*Attendee feedback from 2024.
Here is a sample of feedback from the last run of the course:
"The teaching was excellent - really clear, using informative examples and practical sessions that really cement your understanding" - course feedback, March 2024
"The combination of synchronous and asynchronous activity was very good. The practical's were very helpful" - course feedback, March 2024
"Very thorough coverage of underlying principles"- course feedback, March 2024
"The course is well structured and the timings worked out. Stephanie is an incredibly experienced and exceptional tutor. She was also really flexible and was able to engage attendees despite challenges of online delivery. I am a Stata-only user, but I think it was really good that the course attempted to accommodate both stats packages" - course feedback, March 2024
Bookings for this course are now closed
The teaching was excellent - really clear, using informative examples and practical sessions that really cement your understanding.
Dates don't work? Just need a refresher?
Find out about the self-paced Materials & Recordings version of this course [UoB only].