Full course description
Date: 8th July, 2026
Modality: In-person
Duration: One day, 9:00am-5:00pm
Price: $550.00 (incl. GST).
This course introduces concepts and methods for longitudinal data analysis (repeated measurements). It begins with data exploration and basic concepts such as age/period/cohort effects and within/between-person comparisons. Participants then learn to fit linear or logistic models to panel data in R or Stata.
Longitudinal studies provide some leverage in establishing direction of causality. The course will describe time-varying confounding and the fitting of marginal structural models to estimate effects of exposures where appropriate.
Course Structure and topics covered:
The single-day course consists of four sessions. After the first three sessions participants will complete exercises and then discuss.
Topics will include: age/period/cohort effects; within- and between- person associations; linear and logistic models for panel data; introduction to issues in causal inference for longitudinal data
Learning Outcomes
Students should be able to:
- Distinguish age, period, and cohor effects conceptually
- Fit linear and logistic regression models to panel data in R or Stata
- Draw casual diagrams showing time-varying and feedback confounding
- Interpret marginal structural models of casual effects
- Express appropriate distrust of casual conclusions in observational data
Who should attend?
Participants should have basic clinical or epidemiology-based training in statistics, plus the ability to fit a logistic regression model in R or Stata and a laptop with suitable software. They should have an interest in human health research.
Payment for short courses is normally by credit card. If you need to pay by invoice or require assistance, please email shortcourses@auckland.ac.nz. Please note the University does not issue individual invoices for amounts less than $500 New Zealand dollars.
By enrolling in a Short Course at the University of Auckland you agree to the Short Course Terms and Conditions