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Longitudinal Structural Equation Modeling (Methodology in the Social Sciences) Hardcover – 10 May 2013

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"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, Vanderbilt University, Tennessee, USA

"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, Tufts University, Massachusetts, USA

"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, The Pennsylvania State University, USA 

About the Author

Todd D. Little, PhD, is Professor of Psychology, Director of the Quantitative Training Program, and a member of the Developmental Training Program at the University of Kansas (KU), where he is also Director of the Center for Research Methods and Data Analysis. He is editor of Guilford's Methodology in the Social Sciences series. Past president of the American Psychological Association's Division 5 (Evaluation, Measurement, and Statistics), Dr. Little organizes and teaches in the renowned KU "Stats Camps" each June.

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Most Helpful Customer Reviews on (beta) HASH(0x932058dc) out of 5 stars 8 reviews
5 of 6 people found the following review helpful
HASH(0x934988ac) out of 5 stars Amazing book that's more like a mentor than a written lecture 7 Dec. 2013
By Wayne Folta - Published on
Format: Hardcover Verified Purchase
This is an amazing book! It's the kind of book you read and then wonder, "Why aren't all statistical books written like this?". What makes it so incredible is the way that the author describes his thought process, experience, and approach to issues. It feels like you're being mentored rather than lectured.

If Amazon let you add a sixth star for just a couple of books over your purchasing history, this one would get my extra star.

As one example of what I mean, he spends five pages discussing the design of the timing of measurements that you will take, and the effects that this timing can have. Many measurements will be taken over a time window, and the location and duration of that window can have different effects. (Effects that SEM is well able to deal with, if you have a good design and a model which takes it into account.) It's really encouraging to read someone who says, "I've been guilty of this thinking in my own past work. ... In my older datasets, I won't know whether they did ... Had I known then what I know now, I would have ... The more I work with researchers and study development chafes, the more I realize ..." As I said, more like a mentor than a lecturer.
HASH(0x935c8288) out of 5 stars This is the best and most useful longitudinal latent variable modeling text that ... 26 Sept. 2015
By glb - Published on
Format: Hardcover Verified Purchase
This is the best and most useful longitudinal latent variable modeling text that I have read. This book has been essential to me in the publication of three papers at this point. In addition, I was able to use sections of the text, especially the chapter on model fit, to address reviewers' suggestions. I also used this text as the primary text in a graduate course on longitudinal SEM. Students found the book extremely helpful with their dissertation research. Finally, Professor Little's writing style is wonderful--he has the unique talent to make complex statistical issues understandable as well as fun to read about!
HASH(0x935c818c) out of 5 stars Extremely well-written! 30 Sept. 2015
By dablo - Published on
Format: Hardcover
Prior to reading this book, I had a hard time with topics such as panel models, longitudinal growth curve modeling, invariance testing, and so on. Upon my first read through, I gained insights into the aforementioned topics which I thought it would take years to garner. Little has a gift for interpreting difficult concepts such that even the most novice learners can feel confident in their knowledge after some time with this book.
HASH(0x935c6a08) out of 5 stars Real world examples and humor 29 Sept. 2015
By Jacob Curtis - Published on
Format: Hardcover Verified Purchase
As far as books on statistical concepts go, this is one of the best. This topic could be taught drly but Dr. Little injects his teaching with real world examples and humor that make it an interesting read. I tried other books to teach me SEM before I found this one and this one is the one that worked for me.
HASH(0x93593924) out of 5 stars Best LSEM Book Out There 30 Sept. 2015
By Sam Meeks - Published on
Format: Hardcover
This book deserves the 100% 5 star rating that it currently has. The explanations are clear and easy to understand. This is the kind of book you want on hand when you're doing your LSEM.
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