Longitudinal Structural Equation Modeling

Methodology in the Social Sciences

by Todd D. Little

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).

386 pages, Hardcover

First published January 1, 2013

Reviews

[Veronica · Rating 5 out of 5]

Another great author with a way of explaining complex topics with plain and accessible language! A very enjoyable read with the right amount of challenge! This definitely helps me go from analysing cross-sectional to longitudinal data. Highly recommend it!

[Donald Schopflocher · Rating 5 out of 5]

State of the art.