This 5-day intensive Longitudinal Data Analysis course has been specifically designed to deepen the specialist knowledge of your research teams and enhance the quality and meaning of the data you use when making crucial business decisions. 

Longitudinal data are essential for understanding:

  • Policy or program impact
  • Change over time 
  • Event occurrence 
  • Causal relationships 

The course delves deeply into topics that are pivotal for organisations that use longitudinal data for research and decision-making. Using an engaging combination of presentations, exercise-based and group activities the course covers the latest in statistical methods, as well as how and where to apply them. The practical hands-on sessions use real-world longitudinal data, from the Household, Income and Labour Dynamics in Australia (HILDA) survey and Growing up in Australia: The Longitudinal Study of Australian Children (LSAC). 

This course is only open to group bookings of 10 or more participants. It can be tailored on request (email us to discuss pricing) for: 

  • In person or online delivery
  • Alternative software preferences (Stata or R-Studio) 
  • In-house or alternative demonstration data (e.g. with your organisation’s data) 

Who this course is for
Social policy, practice and research professionals, including those from government, NGO and research organisations, who want to learn how to leverage longitudinal data to enhance knowledge, guide decision making, and shape policy and practice. Previous experience with linear and logistic regression is desirable but not essential (we will revise these foundational techniques in the course). Familiarity with Stata or R Studio is also valuable but not required.  

Topics covered 

  • Revision of linear and logistic regression
  • Data structures for longitudinal data 
  • Descriptive analysis of longitudinal data 
  • Random effects and fixed effects models for panel data 
  • Growth modelling 
  • Event history analysis (also called survival analysis) 
  • Evaluating model fit 
  • Choosing appropriate models for longitudinal data 

Learning objectives 

  • Understand insights and advantages that come from longitudinal data 
  • Develop familiarity with data setup and preparation for longitudinal data
  • Learn how to apply advanced statistical approaches to longitudinal data, including panel data models, growth models, and event history analysis using either Stata or R Studio
  • Gain knowledge of how to select models for longitudinal data that are suited to your research questions and data
  • Understand limitations and constraints of longitudinal data 

    Course dates
    This course is only open to group bookings of 10 or more participants. It can be tailored for in-person or online delivery (with organisational licences for stata). Email us to discuss.

    Custom & Group enquiries



      Dr Matthew Curry is a sociologist and research fellow at ISSR. He studies inequality in education and labor market outcomes and intergenerational stratification processes. He has experience with a range of econometric techniques including propensity score methods, event history techniques, and multilevel models. Much of his work uses longitudinal data sets, including large household panel survey, to study parents’ and children’s long-term socioeconomic outcomes.


      Dr Alice Campbell is a sociologist and Life Course Centre Research Fellow based at ISSR. She has extensive experience working with large, longitudinal datasets, including the Australian Longitudinal Study on Women’s Health (ALSWH), the Longitudinal Study of Australian Children (LSAC), and the Household, Income and Labour Dynamics of Australia (HILDA) Survey. In her work, she uses a range of methods for longitudinal data analysis including random- and fixed-effect panel regression, sequence analysis, path analysis, and growth curve models. Alice’s research is focused on understanding the production of inequalities by sexual identity and gender from a life-course perspective.



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      The course introduced me to an additional suite of analytical tools, which adds to my range of analytical options and will provide me with additional “leads when looking for patterns in data”.  My attendance at this course is the result of a recommendation by a co-worker who took the course - and I, in turn, will be sure to also recommend this course to others. I recommend this course to anyone who has an interest (or need) to determine patterns in the data which reflects events or characteristics over a period of time.  Useful juicy stuff!   
      Dr. Travis Anderson-Bond, Youth Justice, Queensland