9781462510160-1462510167-Longitudinal Structural Equation Modeling (Methodology in the Social Sciences Series)

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

ISBN-13: 9781462510160
ISBN-10: 1462510167
Edition: First Edition
Author: Todd D. Little
Publication date: 2013
Publisher: The Guilford Press
Format: Hardcover 386 pages
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Book details

ISBN-13: 9781462510160
ISBN-10: 1462510167
Edition: First Edition
Author: Todd D. Little
Publication date: 2013
Publisher: The Guilford Press
Format: Hardcover 386 pages

Summary

Longitudinal Structural Equation Modeling (Methodology in the Social Sciences Series) (ISBN-13: 9781462510160 and ISBN-10: 1462510167), written by authors Todd D. Little, was published by The Guilford Press in 2013. With an overall rating of 3.7 stars, it's a notable title among other Statistics (Education & Reference, Research & Theory, Nursing, Methodology, Social Sciences) books. You can easily purchase or rent Longitudinal Structural Equation Modeling (Methodology in the Social Sciences Series) (Hardcover) from BooksRun, along with many other new and used Statistics books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $6.99.

Description

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).

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