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About the Book

Longitudinal data is essential for understanding the world around us. It allows us to investigate changes over time and obtain better causal estimates. Nevertheless, this type of data is also more complex, making it difficult to manipulate, explore, and analyse.

This book covers all the key skills necessary for working with longitudinal data, employing a hands-on approach and real-world data. To ensure a solid foundation, it begins by introducing the basics of R, regression modelling, path analysis, and concepts of longitudinal data. It then covers how to efficiently prepare longitudinal data by importing, recoding and reshaping data. This is followed by a comprehensive introduction to data exploration using tables, summary statistics and visualisations. The book also provides an in-depth guide to state-of-the-art statistical models for analysing longitudinal data, including the multilevel model for change and the latent growth model. It discusses practical challenges to conducting longitudinal analysis, such as missing data, measurement error, separating age-period-cohort effects, presenting results, and following a reproducible workflow.

About the Author

Alexandru Cernat

@cernat_a

Alexandru Cernat is a Professor at the University of Manchester, specialising in collecting and analysing longitudinal data.

Over the past decade, he has published over 50 papers and book chapters using advanced statistical models to investigate how people and societies change.

He has extensive experience teaching survey methodology and longitudinal data analysis to researchers and practitioners worldwide, including for organisations such as the European Survey Research Association, the Social Research Association, GESIS, Essex Summer School and the International Program in Survey and Data Science.

He is also the founder of longitudinalanalysis.com, a platform developed to help researchers and analysts learn how to collect, clean, and analyse longitudinal data with confidence.