Deepen your specialist knowledge of longitudinal approaches

Very large crowd in shape of upward arrow with people aboveThis five-day intensive 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.

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) longitudinal survey, and Growing up in Australia: The Longitudinal Survey of Australian Children (LSAC).

Topics covered

  • Longitudinal data - structures and management
  • Exploratory longitudinal data analysis
  • Panel regression - Pooled OLS, fixed-effect, random-effect and hybrid models
  • Multi-level data and frameworks applied to longitudinal data
  • Event history analysis
  • Model choice for longitudinal data

Learning objectives

  • Understand the advantages of using longitudinal data for research and decision-making
  • Manage longitudinal datasets and prepare these for statistical analysis
  • Understand the different approaches that can be used to model multivariate relationships with longitudinal data (e.g. fixed and random-effect regression models)
  • Recognise hierarchical data and the relevance of multilevel models
  • Understand how multilevel models can be used to analyse variation and trends in growth over time with longitudinal data
  • Understand how to model duration until an event occurs, using event-history analysis
  • Determine which modelling approach is most appropriate for different types of research questions
  • Effectively present longitudinal data analyses results to non-technical audiences

Who is this course for

Analysts and researchers in government, private organisations and universities who want to develop their skills in the analysis and interpretation of longitudinal data.


  • Working knowledge of ordinary least squares (OLS) regression techniques.
  • Stata® software experience is desirable but not necessary.

Course dates

Monday, 9 December - Friday, 13 December 2019 
2020 dates TBA

For Custom and Group courses (10 participants or more) - Email us to discuss

Fees (incl. GST)

$3,465 - Early Bird (book and pay one month out)
$4,180 - After Early Bird discount expires
$3,344 - Groups (3 or more, price per person)
$3,135 - Students
(Fees include course materials and full-day catering)

By registering to attend this course you are agreeing to our terms and conditions.

    PresentersDr Paco Perales
    Dr Francisco (Paco) Perales is a sociologist with expertise in longitudinal research methods. His research uses a life course approach to better understand gender-based socioeconomic inequality, subjective wellbeing, quality of life, social disadvantage, and gender and sexual identity inequalities. He has methodological expertise in advanced quantitative research methods, and conducting econometric analysis of cross-sectional and longitudinal large-scale social surveys. Paco has taught longitudinal data analysis, multi-level modelling and quantitative research skills in undergraduate programs at the University of Queensland, and supervises students at the Honours and PhD level.

    Dr Martin O'Flaherty is an experienced sociologist and one of ISSR’s key researchers in life Dr Martin O'Flahertycourse analysis and family dynamics. Martin is an ISSR Research Fellow in Family Dynamics within the ARC Centre of Excellence for Children and Families across the Life Course (the Life Course Centre) and an exceptional emerging sociologist who has already been published in the top-tier journal Demography.  Martin’s recent research investigates longitudinal patterns of time-use among Australian children, background factors (such as class and family structure) that predict time-use patterns, and associations between child time-use and developmental, achievement, and health outcomes in adolescence. He is also aiming to identify health, labour market, and other consequences of different fertility timings. Martin has extensive high level experience in quantitative analysis and data collection, and substantial experience managing large projects including diverse stakeholder groups.

    UQ's Institute for Social Science Research, Cycad Building, 80 Meiers Road, Indooroopilly, Brisbane, Australia