Training Calendar

Introduction to Generalised Linear Mixed Models using Stata

Online 2 days (27th September 2021 - 28th September 2021) Stata Intermediate, Introductory
Delivered by: James Gallagher; Sandro Leidi
Medical statistics, Statistics

Presented by Sandro Leidi & James Gallagher

This course is running online, via Zoom.

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 examples, generally drawn from medical and health related fields. Specific applications, such as repeated measurements and multi-centre trials will also be considered. For example, 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 based practicals.

Note this course does not cover marginal or GEE type models for repeated measurements.

Course Timetable

Session One Session Two Q&A with Instructor
10am-1pm 2pm-5pm 5pm-5:30pm
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Day 1

  1. Review of generalised linear models and linear mixed models.
  2. Mixed models for binary response data.
  3. Introduction to dedicated Stata commands for fitting generalised linear mixed models.
  4. Hypothesis testing features in Stata.

Day 2

  1. Model fitting methods and computational issues.
  2. Mixed models for count response data.
  3. Mixed models for ordered categorical response data.
  4. Question and answer session.

Prerequisites

It is assumed that delegates:

  • Are Stata users;
  • Are familiar with the practical use of both linear mixed models and generalised linear models;
  • Have experience of fitting these models in Stata and interpreting the results.

Pre-course reading:

Chapter 8: Mixed Models for Binary Data in Collett, D. (2003). Modelling Binary Data. 2nd Edition. Chapman & Hall/CRC.

Verbeke, G. and Molenberghs, G. (2013). Generalized Linear Mixed Models -Overview. In: Scott, M.A., Simonoff, J.S. and Marx, B.D. ed. The SAGE Handbook of Multilevel Modeling. SAGE Publications Ltd, Chapter 8.

Post-course reading

Rabe-Hesketh, S. and Skrondal, A. (2012). Multilevel and Longitudinal Modeling Using Stata. Volume 2: Categorical Responses, Counts and Survival. 3rd Edition. Stata Press. (Note this course does not make use of the gllamm Stata program.)

Stroup, W.W. (2013). Generalized Linear Mixed Models. Modern Concepts, Methods and Applications. CRC Press.

Terms & Conditions

  • Student registrations: Attendees must provide proof of full time student status at the time of booking to qualify for student registration rate (valid student ID card or authorised letter of enrolment).
  • Additional discounts are available for multiple registrations.
  • Delegates are provided with temporary licences for the principal software package(s) used in the delivery of the course. It is essential that these temporary training licenses are installed on your computers prior to the start of the course.
  • Payment of course fees required prior to the course start date.
  • Registration closes 1 calendar day prior to the start of the course.
    • 100% fee returned for cancellations made more than 28-calendar days prior to start of the course.
    • 50% fee returned for cancellations made 14-calendar days prior to the start of the course.
    • No fee returned for cancellations made less than 14-calendar days prior to the start of the course.

The number of attendees is restricted. Please register early to guarantee your place.

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