Introduction to Linear and Logistic Regression Models

Coronavirus (COVID-19) information

The Short Course Programme in Population Health Sciences has been temporarily suspended.


We anticipate opening bookings in late November 2020.

Information on this page relates to the last run of the course and is for reference only. 

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We may need to make responsive changes to our future programme to follow the latest Public Health, Government and University guidance on coronavirus (COVID-19).

Please be aware that all information about short courses planned for 2021 is provisional and subject to change.

Course dates

11 - 15 May 2020

Course duration

5 days (approximately 14 hours of lectures and 15 hours of practicals).
Registration will start at 9am on the first day, the courses will finish by 4pm on the final day.

Course tutors

Dr Stephanie MacNeill and Professor Chris Metcalfe (course organisers) and others.

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.

Course objectives

By the end of the course, students will: 

  • 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 commands to run these models, and a thorough understanding of the output generated from such a package;
  • know the basis on which analytical strategy and model choice is made, and how the results should be interpreted.

Who 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.

Prerequisites: Participants should have knowledge of statistical methods and their implementation in Stata of at least the level achieved in the 'Introduction to Statistics' short course.   

Course outline

  • Revision of basic methods in a statistical modelling framework
  • Terminology in regression modelling
  • Indicator variables to incorporate categorical explanatory variables
  • Univariable and multivariable regression
  • Common features of linear and logistic regression models
  • Interpretation of model coefficients as differences in means or odds ratios
  • Adjustment for confounding and exploring effect modification (interaction) in multivariable regression
  • Comparing models with Wald tests and likelihood ratio tests
  • Model assumptions
  • Analytical strategies

Please note: Practical sessions of this course will be held in a computer lab, so you do not need to bring a laptop. Stata v15 will be used during the course.

Recommended reading

Course handouts will cover all material.

All participants will be expected to have a copy of 'Essential Medical Statistics' with them during the course:

  • Kirkwood BR, Sterne JAC. Essential Medical Statistics, 2nd ed. Oxford: Blackwell Science, 2003.

We will let you know how to buy a copy at a discounted rate when we confirm your place on the course.

The practicals were well thought through and taught me a lot. I liked that there were lots of opportunities to ask questions and to request further topics to be reiterated or included in the final lecture.

Course feedback, June 2019

Course fee


More information on course fees, fee waivers and reduced prices.

Course venue

Bristol Medical School
Canynge Hall
39 Whatley Road
United Kingdom

Map and directions

Course refreshments

We provide morning and afternoon refreshment breaks, including tea and coffee, biscuits and fresh fruit.

If you have specific dietary needs we ask that you let us know in advance.

Lunch is not included. There are a range of local cafes and supermarkets nearby for students to purchase lunch. 


Information about accommodation in the area.


For further information please email

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