Applied Longitudinal Analysis is an essential resource for statisticians, data scientists, and researchers who need to analyze data that are collected over time. This comprehensive book provides an up-to-date treatment of methods and models used in the analysis of longitudinal data, a key area of growth in the statistical sciences due to the increasing availability of repeated measures data.
The book emphasizes practical applications and includes a wide array of methodologies supported by real-world examples. A distinguishing feature of this work is its focus on teaching readers how to approach real data problems using modern statistical techniques. Each chapter is structured to guide the reader through important concepts in a clear and organized manner.
Rich in content, yet accessible to those who may be less familiar with statistical terminologies, this book elucidates longitudinal analysis techniques ranging from simple models to complex models. Readers will find the in-depth explanations valuable as they navigate through advanced topics like multilevel modeling, non-linear models, and generalized estimating equations.
With a priority on understanding and implementing the latest methods, this book is an indispensable guide for anyone tasked with understanding trends and changes across time. Useful both as a textbook and a reference book, it paves an effective path from comprehending basic methodologies to grasping intricate longitudinal data analysis principles.