Analysis of Longitudinal Data with Examples

This book discusses modern approaches to inference, including the links between estimators and efficient statistical models, with practical examples of R-codes and packages applied to case-studies from various areas.

Format: Hardback
Length: 226 pages
Publication date: 28 January 2022
Publisher: Taylor & Francis Inc

The field of methodology in longitudinal data analysis is experiencing rapid advancements. While there are a number of introductory textbooks available for students and practicing statisticians, there is a scarcity of intermediate/advanced level texts that provide comprehensive coverage of the latest methods in correlated data inference. This book aims to bridge this gap by presenting a comprehensive discussion of modern approaches to inference, including the connections between estimator theories and various efficient statistical models, such as likelihood-based approaches.

The theory will be supported with practical examples of R-codes and R-packages applied to intriguing case studies from diverse fields. Some of the key features of this book include:

•Up-to-date coverage of the most recent methods in longitudinal data analysis.
•Use of simple examples to illustrate complex methods, making the content accessible to a wide range of readers.
•Utilization of real data from various domains to demonstrate the practical applications of the discussed techniques.
•Examples are accompanied by R-code, allowing readers to replicate the analyses and gain hands-on experience with the statistical methodologies.

By offering a comprehensive and practical guide to inference in longitudinal data analysis, this book will be valuable to students, researchers, and practitioners in the field. It will serve as a valuable resource for those seeking to stay updated with the latest developments and apply advanced statistical techniques to their research.

Weight: 514g
Dimension: 162 x 241 x 21 (mm)
ISBN-13: 9781498764605