Longitudinal Structural Equation Modeling PDF

Rating: (1 reviews) Author: Todd D. Little ISBN : 9781462510160 New from $50.19 Format: PDF

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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).

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• Series: Methodology in the Social Sciences
• Hardcover: 386 pages
• Publisher: The Guilford Press; 1 edition (March 25, 2013)
• Language: English
• ISBN-10: 1462510167
• ISBN-13: 978-1462510160
• Product Dimensions: 7 x 10 inches
• Shipping Weight: 1.9 pounds (View shipping rates and policies)

Longitudinal Structural Equation Modeling PDF

Prof. Little is among the leading statisticians, especially, in the art of structural equation modeling. In his new book: "Longitudinal Structural Equation Modeling" he adds several aspects. First, he shares his own experience with the readers such that the text becomes very practical and many operational advices are given which save the muddling through time. He is very innovative in introducing several measurement instruments usually not common among lay users of statistics. This introduction stimulates experimentation with alternative models and more complex structures. Overall these advantages, Prof. Little use friendly language and a generous sense of humor, some is ready for quoting, though reading the book require a great deal of efforts to clearly understand the meaning of all terms, figures, and text. In my work as a statistical consultant, I find the book extremely helpful and I cite it repeatedly. Dr. Gabriel Liberman – Data-Graph Statistical Consulting at: www.data-graph.com .

By Dr. Gabriel Liberman