Online training


Online training
BYO computer, your house, your address


28 May 2021


9:00 am - 5:00 pm

AQM Longitudinal analysis in R

This Advanced Quantitative Methods training is open to all ESRC and non-ESRC funded students within the seven WRDTP partner institutions. Students are welcome from all seven interdisciplinary Pathways.

The aim of this course is to give an introduction to longitudinal data and ways that you might analyse these data, as well as the practical skills necessary to begin doing this.

The course will start by introducing different types of longitudinal data and different types of questions that can be answered with these data.

It will then introduce different methods for analysing longitudinal data, focusing on analysing continuous outcomes. Students will learn about fixed and random effects models for longitudinal data and growth curve models.

Interspersed with the lectures, there will be practical sessions where students will learn to run longitudinal analyses using these methods R.

The course will also introduce models for discrete outcomes and event history analysis although less time will be spent on this. There will be opportunities to discuss student’s own data and research questions.

Following this training students will

  • Gain an understanding of different types of longitudinal data
  • Be able use and interpret models for longitudinal outcomes such as fixed and random effects models
  • Be able to use R to run longitudinal analysis
  • Gain confidence to start analysing their own longitudinal data

Please note: It is assumed that attendees will have a familiarity with R and linear regression – please visit the VIRE on the WRDTP website where you can view a recorded Introduction to R session. You will need to download R and R Studio onto your computer before the course (links will be provided to attendees).

Workshop leader

Dr Gwilym Owen

Research Associate, University of Liverpool

This training session will be delivered via Blackboard Collaborate. 

PLEASE NOTE: Our online training sessions will be recorded and will be available on the VIRE in an edited format for those students who cannot attend. If you wish to join this session but do not wish for your contributions to be included in the edited VIRE resource, please ensure that you select NO when prompted in the online booking form regarding recording.