Longitudinal Analysis

Longitudinal methods, made clear

Master Longitudinal Data

Learn how to clean, model, and visualise change over time with expert guidance, practical tools, and real-world data.

Visualising patterns for longitudinal data

Testimonials

Analysing longitudinal data is challenging… no other book compiles the relevant topics in such a pedagogical way… a must-read for both people new to longitudinal data analysis and those looking to improve their existing knowledge.

Kim Backström, PhD student, Åbo Akademi, Finland

I had a longitudinal dataset that was ideal for answering an important research question in my field, but I had no experience with longitudinal analyses. After reading this book, I felt confident enough to run the analyses myself. The paper is now ready to be submitted. I was honestly surprised that a book could help someone with zero background in longitudinal analysis do complex analyses for a real research project.

Omid Ghasemi, Postdoctoral Research Associate, University of New South Wales

Thoroughly recommend anything taught by Alex.

Michelle Degli Esposti, Postdoctoral Researcher, University of Oxford

I owe Alex’s 2018 course my ‘re-birth’ as an R data manager and analyst.

Teresio Poggio, Research Assistant, University of Trento

What I really liked about the book was how unique it was… accessible… excellent, particularly around multi-level modelling.

Emily Lowthian, Lecturer in Education, Swansea University

Author & Platform Creator

I’m Alex Cernat, Professor of Methodology and Social Data Science at the University of Manchester, specialising in collecting and analysing longitudinal data.

Over the past decade, I’ve published over 50 papers and book chapters using advanced models to study how people and societies change.

This website combines everything I’ve learned to offer you practical tools, real-world examples, and clear explanations for mastering longitudinal data.

Learn more

Get the Book

Longitudinal Data Analysis Using R

The book covers all the key skills needed to prepare, explore, and analyse longitudinal data. It interweaves explanations of key concepts, statistical modelling, code and visualisations using real-world data.

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