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Book Cover
E-book
Author Beaujean, A. Alexander, author.

Title Latent variable modeling using R : a step-by-step guide / A. Alexander Beaujean
Published New York : Routledge, Taylor & Francis Group, 2014
©2014
Online access available from:
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Description 1 online resource (xii, 205 pages) : illustrations
Contents Cover; Title; Copyright; Contents; Author Biography; Preface; 1 Introduction to R; 1.1 Background; 1.2 Hints for Using R; 1.3 Summary; 1.4 Exercises; 1.5 References & Further Readings; 2 Path Models and Analysis; 2.1 Background; 2.2 Using R For Path Analysis; 2.3 Example: Path Analysis using lavaan; 2.4 Indirect Effect; 2.5 Summary; 2.6 Writing the Results; 2.7 Exercises; 2.8 References & Further Readings; 3 Basic Latent Variable Models; 3.1 Background; 3.2 Latent Variable Models; 3.3 Example: Latent Variable Model with One Latent Variable; 3.4 Example: Structural Equation Model; 3.5 Summary
3.6 Writing the Results3.7 Exercises; 3.8 References & Further Readings; 4 Latent Variable Models with Multiple Groups; 4.1 Background; 4.2 Invariance; 4.3 Group Equality Constraints; 4.4 Example: Invariance; 4.5 Using Labels for Parameter Constraints; 4.6 Example: Genetically Informative Design; 4.7 Summary; 4.8 Writing the Results; 4.9 Exercises; 4.10 References & Further Readings; 5 Models with Multiple Time Periods; 5.1 Background; 5.2 Example: Latent Curve Model; 5.3 Latent Curve Model Extensions; 5.4 Summary; 5.5 Writing the Results; 5.6 Exercises; 5.7 References & Further Readings
6 Models with Dichotomous Indicator Variables6.1 Background; 6.2 Example: Dichotomous Indicator Variables; 6.3 Summary; 6.4 Writing the Results; 6.5 Exercises; 6.6 References & Further Readings; 7 Models with Missing Data; 7.1 Background; 7.2 Analyzing Data With Missing Values; 7.3 Example: Missing Data; 7.4 Summary; 7.5 Writing the Results; 7.6 Exercises; 7.7 References & Further Readings; 8 Sample Size Planning; 8.1 Background; 8.2 Summary; 8.3 Writing the Results; 8.4 Exercises; 8.5 References & Further Readings; 9 Hierarchical Latent Variable Models; 9.1 Background; 9.2 Summary
9.3 Writing the Results9.4 Exercises; 9.5 References & Further Readings; Appendix A Measures of Model Fit; Appendix B Additional R Latent Variable Model Packages; Appendix C Exercise Answers; Glossary; Author Index; Subject Index; R Function Index; R Package Index; R Dataset Index
Summary This step-by-step guide is written for R and latent variable model (LVM) novices. Utilizing a path model approach and focusing on the lavaan package, this book is designed to help readers quickly understand LVMs and their analysis in R. The author reviews the reasoning behind the syntax selected and provides examples that demonstrate how to analyze data for a variety of LVMs. Featuring examples applicable to psychology, education, business, and other social and health sciences, minimal text is devoted to theoretical underpinnings. The material is presented without the
Analysis data analysis
gegevensanalyse
mathematical models
modeling
modelleren
statistical analysis
statistische analyse
wiskundige modellen
Mathematical Models, Simulation Models
Wiskundige modellen, simulatiemodellen
Bibliography Includes bibliographical references and indexes
Notes Print version record
Subject Latent structure analysis -- Data processing
Latent variables -- Data processing
R (Computer program language)
MATHEMATICS -- Applied.
MATHEMATICS -- Probability & Statistics -- General.
R (Computer program language)
Form Electronic book
ISBN 1306785790
1315869780
131797073X
9781306785792
9781315869780
9781317970736