Parceling In Structural Equation Modeling
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Parceling in Structural Equation Modeling
Author: Todd D. Little
language: en
Publisher: Cambridge University Press
Release Date: 2022-07-28
Parceling is pre-modeling strategy to create fewer and more reliable indicators of constructs for use with latent variable models. Parceling is particularly useful for developmental scientists because longitudinal models can become quite complex and even intractable when measurement models of items are fit. In this Element the authors provide a detailed account of the advantages of using parcels, their potential pitfalls, as well as the techniques for creating them for conducting latent variable structural equation modeling (SEM) in the context of the developmental sciences. They finish with a review of the recent use of parcels in developmental journals. Although they focus on developmental applications of parceling, parceling is also highly applicable to any discipline that uses latent variable SEM.
Handbook of Structural Equation Modeling
Author: Rick H. Hoyle
language: en
Publisher: Guilford Publications
Release Date: 2023-02-17
"This accessible volume presents both the mechanics of structural equation modeling (SEM) and specific SEM strategies and applications. The editor, along with an international group of contributors, and editorial advisory board are leading methodologists who have organized the book to move from simpler material to more statistically complex modeling approaches. Sections cover the foundations of SEM; statistical underpinnings, from assumptions to model modifications; steps in implementation, from data preparation through writing the SEM report; and basic and advanced applications, including new and emerging topics in SEM. Each chapter provides conceptually oriented descriptions, fully explicated analyses, and engaging examples that reveal modeling possibilities for use with readers' data. Many of the chapters also include access to data and syntax files at the companion website, allowing readers to try their hands at reproducing the authors' results"--
Longitudinal Structural Equation Modeling
Author: Todd D. Little
language: en
Publisher: Guilford Publications
Release Date: 2024-01-02
This valuable book is now in a fully updated second edition that presents the latest developments in longitudinal structural equation modeling (SEM) and new chapters on missing data, the random intercepts cross-lagged panel model (RI-CLPM), longitudinal mixture modeling, and Bayesian SEM. Emphasizing a decision-making approach, leading methodologist Todd D. Little describes the steps of modeling a longitudinal change process. He explains the big picture and technical how-tos of using longitudinal confirmatory factor analysis, longitudinal panel models, and hybrid models for analyzing within-person change. User-friendly features include equation boxes that translate all the elements in every equation, tips on what does and doesn't work, end-of-chapter glossaries, and annotated suggestions for further reading. The companion website provides data sets for the examples--including studies of bullying and victimization, adolescents' emotions, and healthy aging--along with syntax and output, chapter quizzes, and the book’s figures. New to This Edition: *Chapter on missing data, with a spotlight on planned missing data designs and the R-based package PcAux. *Chapter on longitudinal mixture modeling, with Whitney Moore. *Chapter on the random intercept cross-lagged panel model (RI-CLPM), with Danny Osborne. *Chapter on Bayesian SEM, with Mauricio Garnier. *Revised throughout with new developments and discussions, such as how to test models of experimental effects.