Longitudinal Data and Research - A deep dive (online)



Organised by:

University of Edinburgh


Professor Vernon Gayle


Intermediate (some prior knowledge)


Laura Marshall

video conference logo

Venue: Online


Across the social sciences there is widespread agreement that longitudinal data (e.g. studies that repeatedly contact participants) provides powerful research resources to examine both social change and social stability. There is now a broad portfolio of longitudinal data available to social science researchers. Many social science research questions can be adequately answered without longitudinal data; however, most research projects will bene?t from the addition of longitudinal data analysis, and some research questions can only feasibly be answered using longitudinal data.

This is an intensive one-day wokshop on longitudinal data and research using statistical methods. The event is intended to be engaging and informative and there will be audience participation and opportunities to ask questions.

Researchers who are at any career stage are welcome.

Course Timings: 09:00 - 16:00

The workshop is specifically designed for social scientists, and social science data and examples will be showcased throughout the workshop. The workshop will focus on the research value of longitudinal data and explore sources of longitudinal data. Participants will be introduced to the analysis of repeated cross-sectional data, duration models and models for panel data. The emphasis will be on interpreting outputs (e.g. from data analysis software packages) and understanding results (e.g. in published papers).

This is not a practical workshop and it does not provide training in the use of data analysis software. It will however provide a strong theoretical foundation for future engagement at practical workshops that are designed to provide hands-on training in data analysis.

Access to specialist software and a high level of mathematical ability are not required, but participants should ideally have undertaken an introductory statistics and data analysis course (e.g. a semester long module as part of a Masters degree) or have attended an NCRM workshop on Statistical Modelling.

This workshop will be at an intermediate level and will cover the following ideas and concepts:

  • The research value of longitudinal data
  • Sources of longitudinal data
  • Analysing repeated cross-sectional data
  • Duration models
  • Panel data models
  • The workflow in longitudinal data analysis
  • Statistical data analysis software

By the end of the course participants will:

  • Have an understanding of longitudinal data
  • Have an understanding of statistical approaches to analysing longitudinal data
  • Understand how to analyse repeated cross-sectional data
  • Understand duration models
  • Understand panel data models
  • Be aware of some statistical data analysis software solutions


The fee per teaching day is: £30 per day for registered students / £60 per day for staff at academic institutions, recognised research institutions and Research Councils researchers, public sector staff and staff at registered charity organisations / £100 per day for all other participants In the event of cancellation by the delegate a full refund of the course fee is available up to two weeks prior to the course. No refunds are available after this date. If it is no longer possible to run a course due to circumstances beyond its control, NCRM reserves the right to cancel the course at its sole discretion at any time prior to the event. In this event every effort will be made to reschedule the course. If this is not possible or the new date is inconvenient a full refund of the course fee will be given. NCRM shall not be liable for any costs, losses or expenses that may be incurred as a result of the cancellation of a course. The University of Southampton’s Online Store T&Cs also continue to apply.

Website and registration:




Longitudinal Data Analysis, Panel data models, Event History Analysis, Duration analysis

Related publications and presentations:

Longitudinal Data Analysis
Panel data models
Event History Analysis
Duration analysis

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