Statistical Services Centre Ltd
  • Home
  • Training
    • Course Registration
    • Terms and Conditions
    • Bespoke Training
    • Mailing List Request
  • Consultancy
    • Expertise
  • Team
    • James Gallagher
    • Sandro Leidi
    • Dankmar Böhning
  • SSC-Stat
  • Resources
  • Contact us
  • Products

Generalised Linear Mixed Models

Overview
Mixed models have become increasingly popular, as they have many practical applications. However, the traditional linear mixed model with normally distributed errors may not always be appropriate for modelling discrete response variables, such as binary data and counts. Typically these types of responses are analysed using generalised linear models such as logistic regression and Poisson regression.
Commonly-used generalised linear models will be extended to deal with multiple error structures, using a variety of scientific examples, including medical applications, such as investigating the presence or absence of adverse events collected in a multi-centre clinical trial.
The emphasis will be on practical understanding, although an outline of the theory will be presented. Practical examples will be used to illustrate the methods, and participants will have the opportunity to fit and interpret models themselves in hands-on computer practicals.

Who Should Attend?
Statisticians who are already familiar with linear mixed models. It will be assumed that participants are regular SAS users, and have a working knowledge of generalised linear models.

How You Will Benefit
You will learn how to formulate generalised linear models with fixed and random effects for a range of situations, and how to fit and interpret them.

What Do We Cover?
  • Review of generalised linear models
  • Mixed models for binary and binomial response data: logistic regression
  • Count data: Poisson and negative binomial regression with mixed effects
  • Ordered categorical response variables: proportional odds model with mixed effects
  • Common fitting methods; inferential procedures
  • Convergence issues and solutions
  • Interpretation of effects in a generalised linear mixed model and prediction
  • Applications such as repeated measurements and multi-centre trials
  • Extensions to non-linear models.

Software
Practical work will be done in: SAS
Note: For practical work, participants must bring their own laptop with a fully licensed version of the software.

Extra Information
Related Courses:
Linear Mixed Models


Course Dates
Next run to be announced

Duration: 2 days
Price: £TBC

Apply Now
(terms and conditions apply)

Return to full course listing
Vertical Divider
  • Home
  • Training
    • Course Registration
    • Terms and Conditions
    • Bespoke Training
    • Mailing List Request
  • Consultancy
    • Expertise
  • Team
    • James Gallagher
    • Sandro Leidi
    • Dankmar Böhning
  • SSC-Stat
  • Resources
  • Contact us
  • Products