Publisher: John Wiley & Sons, August 2011
Since the publication of the first edition, the authors have solicited feedback from both the instructors who use the book as a text for their courses as well as the researchers who use the book as a resource for their research. Thus, the improved Second Edition of Applied Longitudinal Analysis features many additions and revisions based on the feedback of readers, making it the go-to reference for applied use in public health, epidemiology, and pharmaceutical sciences.
Applied Longitudinal Analysis, Second Edition presents modern methods for analyzing data from longitudinal studies and now features the latest state-of-the-art techniques. The book emphasizes practical, rather than theoretical, aspects of methods for the analysis of diverse types of longitudinal data that can be applied across various fields of study, from the health and medical sciences to the social and behavioral sciences.
The authors incorporate their extensive academic and research experience along with various updates that have been made in response to reader feedback. The Second Edition features six newly-added chapters that explore topics currently evolving in the field, including:
Each chapter presents the methods in the setting of applications to data sets drawn from the health sciences; in addition, new problem sets have been added to many chapters. This accompanying website features sample programs and computer output using SAS®, Stata®, and R, as well as data sets and supplemental slides to facilitate a complete understanding of the material.
With its strong emphasis on multidisciplinary applications and the interpretation of results, Applied Longitudinal Analysis, Second Edition is an excellent book for courses on statistics in the health and medical sciences at the upper-undergraduate and graduate levels. It also serves as a valuable reference for researchers and professionals in the medical, public health, and pharmaceutical fields as well as the social and behavioral sciences who would like to learn more about analyzing longitudinal data.