The course will be run over 3 days via Zoom sessions
- DAY 1 - March 21, 2022:9am - 3pm (6 hours + 1 hour break)
- DAY 2 - March 22, 2022: 9am - 2pm (4 hours + 1 hour break)
- DAY 3 - March 23, 2022: 9am - 2pm (4 hours + 1 hour break)
In this course, you will learn about the commonly used regression models in longitudinal data analysis. The focus will be on multilevel mixed effects and Generalized Estimating Equations models but there will also be examples for fixed and random effects models, hybrid and Mundlak models, the mixed-effects location-scale, conditional logistic, and segmented linear regression models.
Almost all examples will use data from population health research exploring the complexities of designing and implementing the most appropriate statistical model and providing a clear interpretation of results. From a simple longitudinal study design to more complex designs such as nested, crossover, repeated measures for both covariates and outcome, interrupted time series and ecological momentary analysis will be covered.
If you have any immediate questions, please contact us via
The full course costs 950 AUD, but you can complete parts of it for lesser cost, e.g., modules 1 and 2 or these modules plus either 3 or 4 or both. WSU students and alumni can contact WesternX for a 50% discount!
What some of our students said during the course's first run
“Learning many new statistical methods and tools, understanding the statistical way of thinking. The teacher’s dedication and very responsive and helpful attitude helped me to achieve and learn a lot from this course. I would say this course is very informative and learning materials are constructed in a way that really facilitated the learning process.” (Student comment, Longitudinal Modelling for Population Health Researchers, Spring 2020)
“The instructor set very important examples while explaining the theory. His quizzes are very important for students to have a clear idea of the topics.” (Student comment, Longitudinal Modelling for Population Health Researchers, Spring 2020)
“He simplified the Stata programming language which really motivated us to learn it better and hence enhanced our skills in use of Stata. He even offered us to meet after the class for deeper understanding of programming which is beyond the scope of the course. He tried his best to give examples to simplify the statistical methods taught in the course.” (Personal Communication, Longitudinal Modelling for Population Health Researchers, Spring 2020)