Longitudinal Structural Equation Modeling (Methodology in the Social Sciences) (Hardcover)

Longitudinal Structural Equation Modeling (Methodology in the Social Sciences) By Todd D. Little, PhD, Noel A. Card, PhD (Foreword by) Cover Image

Longitudinal Structural Equation Modeling (Methodology in the Social Sciences) (Hardcover)


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Featuring actual datasets as illustrative examples, this book reveals numerous ways to apply structural equation modeling (SEM) to any repeated-measures study. Initial chapters lay the groundwork for modeling a longitudinal change process, from measurement, design, and specification issues to model evaluation and interpretation. Covering both big-picture ideas and technical "how-to-do-it" details, the author deftly walks through when and how to use longitudinal confirmatory factor analysis, longitudinal panel models (including the multiple-group case), multilevel models, growth curve models, and complex factor models, as well as models for mediation and moderation. User-friendly features include equation boxes that clearly explain the elements in every equation, end-of-chapter glossaries, and annotated suggestions for further reading. The companion website (www.guilford.com/little-materials) provides datasets for all of the examples--which include studies of bullying, adolescent students' emotions, and healthy aging--with syntax and output from LISREL, Mplus, and R (lavaan).
Todd D. Little, PhD, is Professor of Educational Psychology and Leadership at Texas Tech University and founding Director of the Texas Tech University Institute for Measurement, Methodology, Analysis, and Policy. Dr. Little is a Fellow of the American Association for the Advancement of Science; the American Psychological Association (APA) Divisions 5, 7, and 15; and the Association for Psychological Science. He is past president of APA Division 5 (Evaluation, Measurement, and Statistics). Dr. Little organizes and teaches in his renowned "Stats Camp" each June. Partly because of the impact and importance of Stats Camp, Dr. Little was awarded the Cohen Award from APA Division 5 for Distinguished Contributions to Teaching and Mentoring.
Product Details ISBN: 9781462510160
ISBN-10: 1462510167
Publisher: The Guilford Press
Publication Date: March 25th, 2013
Pages: 386
Language: English
Series: Methodology in the Social Sciences

"It is rare for a scholar or a teacher to simultaneously demonstrate wisdom, erudition, vision for the future of the field, and the capacity to explain complex ideas and methods to beginners, while also advancing the skill sets of seasoned researchers. Yet these valued attributes are all found in abundance in this volume. This is more than a book about longitudinal SEM; it is a guide to understanding and conducting good science. If any book can be identified as a classic on publication, this one certainly can."--Richard M. Lerner, PhD, Bergstrom Chair in Applied Developmental Science, and Director, Institute for Applied Research in Youth Development, Tufts University


"Novices and experts alike will learn something new from this book. Little is a born teacher, and it shows in his writing. His approach assumes little background knowledge and provides an entrée to the literature for students and researchers who want to know more. Examples from Little's experience as an applied researcher make the concepts concrete and accessible. This is an ideal text to accompany graduate courses on SEM or longitudinal data analysis and a useful reference for researchers who want to add longitudinal SEM to their methodological toolboxes."--Kristopher J. Preacher, PhD, Department of Psychology and Human Development, Vanderbilt University

"Little has used his gifts as a researcher, teacher, and writer to create a wonderfully accessible volume that will benefit applied researchers and graduate students alike. Each chapter is complete with highly readable explanations, fresh and interesting examples drawn from the author's own considerable experience, beautifully detailed figures, practical modeling tips and tricks, and extensive supporting materials on the Web, all woven together with welcome doses of humor and personality."--Gregory R. Hancock, PhD, Department of Human Development and Quantitative Methodology, University of Maryland

"Little leads readers through a thoughtful and pragmatic approach to SEM by explaining how to think about longitudinal designs, weigh modeling options, and make informed decisions. Developed in both conceptual and technical terms, and illustrated with social science examples, this book is particularly suited to those who follow words and sentences more easily than they track symbols and mathematical operators."--Melissa Hardy, PhD, Department of Sociology, The Pennsylvania State University