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.

By the end of the course participants should:

1. have a thorough conceptual understanding of linear and logistic regression;
2. appreciate the common threads running through these methods, including stratified analysis, different options for handling explanatory variables, and concepts such as confounding and interaction;
3. have a working knowledge of the Stata commands to run these models, and a thorough understanding of the output generated from such a package; and
4. know the basis on which analytical strategy and model choice is made, and how the results should be interpreted.

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.

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.

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.

To make sure the course is suitable for you and you will benefit from attending, please ensure you meet the following prerequisites before booking:

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.

Participants are granted access to our virtual learning platform (Blackboard) approximately 1 week 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.

100% of attendees recommend this course*.
*Attendee feedback from 2022-2023.

Here is a sample of feedback from the last run of the course:

"Excellent teaching from Stephanie, she is clearly very knowledgeable and had great examples to try and make the concepts more understandable".
Course feedback, March 2023

"Stephanie was incredibly accommodating, providing additional resources where needed. She created a safe environment where one could ask questions without feeling stupid. She had a fantastic energy and was positive/enthusiastic".
Course feedback, March 2023

"Really excellent tutoring, and a good balance of talks and practicals".
Course feedback, March 2023

"The balance of lectures and practical activities was good, and the technical content was explained by Stephanie in a really clear way, many thanks indeed".
Course feedback, March 2023

"Stephanie was knowledgeable and clear facilitator. Combining lectures and practicals worked well".
Course feedback, March 2023

"Excellent course. Stephanie was absolutely amazing. I felt the course structure was great. Really comprehensive but moved at a slow enough pace to allow me to get my head around the different concepts".
Course feedback, March 2023

"It was a great refresher but I also learned many new things, I will use logistic regressions in my PhD and I feel more confident now".
Course feedback, March 2023

"Feel so much more confident in planning and interpreting findings now, and basic knowledge of stat commands".
Course feedback, March 2023