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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).
Link to resource: https://www.amazon.com/Longitudinal-Structural-Equation-Modeling-Methodology/dp/1462510167?ie=UTF8&psc=1&redirect=true&ref_=oh_aui_detailpage_o03_s00
Type of resources: Textbook
Education level(s): College / Upper Division (Undergraduates), Graduate / Professional, Career /Technical
Primary user(s): Student, Teacher, Researcher
Subject area(s): Applied Science, Math & Statistics, Social Science