Introduction to Linear and Logistic Regression Models

Course dates

8-12 May 2017.

Course duration: 5 days (approximately 28 hours teaching).
Registration will start at 9.00am on the first day, the course will finish by 4.00pm on the final day.

Course tutors

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

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. 

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 will not need to bring a laptop. Stata v14 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. The book can be purchased at a discounted rate, instructions on how to purchase the book will be sent once your place has been confirmed on the course.

Booking

Make a booking

PAID: Limited places available.

FREE: Fully booked, waiting list in operation.

Course fees

£1,100

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

Course venue

School of Social and Community Medicine
Canynge Hall
39 Whatley Road
Bristol
BS8 2PS
United Kingdom

Map and directions

Lunch and refreshments

Coffee, tea, fruit and biscuits will be available to all students. A light lunch is provided for all paying participants. Please let us know if you have any dietary requirements.

Accommodation

Information about accommodation.

Contacts

For further information please email short-course@bristol.ac.uk