Longitudinal Data Analysis Using R

Longitudinal data offer unique insights into the world around us, such as enabling the exploration of individual-level change and facilitating causal inference. Nevertheless, they can be complex. This book provides a hands-on introduction to working with longitudinal data, covering all essential skills needed and guiding readers through each stage. It begins with the foundations. An introduction to R guides readers from the basics of this popular statistical software to applications of importing, merging, reshaping, and cleaning complex longitudinal data. Readers then learn how to explore longitudinal data using tables, summaries, and visualisations before covering the statistical foundations of regression and path analysis. The book then covers the most popular models for analysing longitudinal data. This includes fixed-, random-, and hybrid-effects models, as well as cross-lagged models. An in-depth discussion of the multilevel model of change and the latent growth model follows. One of the book's unique contributions is its focus on tackling real-world challenges to working with longitudinal data. This is especially true of the last three chapters, which cover missing data, measurement error, and how to present results in a reproducible way. Students can follow along with the code in the book by downloading the data from the UK Data Archive. Students can also access the code used in the book, as well as code to reproduce the results in alternative software such as Mplus and Stata. Reader Testimonials Analysing longitudinal data is challenging, and while there has been a lot written on the subject before, no other book compiles the relevant topics in such a pedagogical way as Alex does in this book. He manages to balance going in-depth while still keeping complex concepts grounded. The book is a must-read for both people new to longitudinal data analysis and those looking to improve their existing knowledge on the subject further. Kim Backström, PhD student, Åbo Akademi, Finland. I purchased this book after attending a short course taught by Dr. Cernat because he was great at clearly and methodically explaining complex longitudinal analysis techniques. This book perfectly replicates his teaching style and has been an incredibly useful resource for me whilst developing code for longitudinal measurement invariance tests and structural equation models in R. Benedict Hignell, PhD Student, University of Essex, UK. 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, Australia. About the Author 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 researchers and practitioners worldwide. 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.