Introduction to Linear and Logistic Regression Models
The 2017-18 short course programme is currently being developed and will be launched on or around 2nd October 2017.
We anticipate running this course again in April 2018.
5 days (approximately 30 hours teaching).
Updated course information to follow
Please be aware that we are currently updating our course information for 2017-18. All course information below is subject to change.
Course aims and objectives
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. 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
Those analysing data from medical, epidemiological, and health services research, who have used simple methods such as t-tests and chi-square tests, but who now wish to use multivariable methods to control confounding, accommodate interaction, and increase statistical power.
Prerequisites: Knowledge of statistical methods and their implementation in Stata of at least the level achieved in the 'Introduction to Statistics’ short course.
- 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 will not need to bring a laptop. Stata v14 will be used during the course.
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.
Bookings for this course are anticipated to open on or around 2nd October 2017.
More information on course fees, fee waivers and reduced prices.
Bristol Medical School
39 Whatley Road
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 email@example.com.