Beginner's Guide to Structural Equation Modeling

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A01=Randall E. Schumacker
A01=Tiffany A. Whittaker
Author_Randall E. Schumacker
Author_Tiffany A. Whittaker
Bifactor Model
Category=GPS
Category=JHB
Category=JMB
Category=JNM
Category=KJ
CFA Model
confirmatory factor analysis
correlation
covariance
educational research methods
eq_bestseller
eq_business-finance-law
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
eq_society-politics
Equivalent Models
Error Covariances
estimates
Factor Model
Full SEM Model
Initial CFA
Initial Measurement Model
introductory SEM guide for graduate students
latent
matrix
measurement invariance
Missing Data
Model Implied Covariance Matrix
modification
Multiple Group
Multiple Group CFA
Multiple Group CFA Model
Multiple Group Model
Multiple Group Path Model
Multiple Imputation
Multiple Linear Regression
multivariate statistics
parameter
psychometrics
QOL Factor
quantitative analysis
Raw Data
sample
SEM Model
SEM Software
Standardized Residual Variance
Structural Equation Modeling
Structural Model
Unstandardized Indirect Effect
variable
variance

Product details

  • ISBN 9780367490157
  • Weight: 940g
  • Dimensions: 178 x 254mm
  • Publication Date: 06 May 2022
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Hardback
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A Beginner’s Guide to Structural Equation Modeling, fifth edition, has been redesigned with consideration of a true beginner in structural equation modeling (SEM) in mind. The book covers introductory through intermediate topics in SEM in more detail than in any previous edition.

All of the chapters that introduce models in SEM have been expanded to include easy-to-follow, step-by-step guidelines that readers can use when conducting their own SEM analyses. These chapters also include examples of tables to include in results sections that readers may use as templates when writing up the findings from their SEM analyses. The models that are illustrated in the text will allow SEM beginners to conduct, interpret, and write up analyses for observed variable path models to full structural models, up to testing higher order models as well as multiple group modeling techniques. Updated information about methodological research in relevant areas will help students and researchers be more informed readers of SEM research. The checklist of SEM considerations when conducting and reporting SEM analyses is a collective set of requirements that will help improve the rigor of SEM analyses.

This book is intended for true beginners in SEM and is designed for introductory graduate courses in SEM taught in psychology, education, business, and the social and healthcare sciences. This book also appeals to researchers and faculty in various disciplines. Prerequisites include correlation and regression methods.

Tiffany A. Whittaker is an Associate Professor in the Department of Educational Psychology at The University of Texas at Austin, USA, where she teaches courses in structural equation modeling, statistical analysis for experimental data, and advanced statistical modeling.

Randall E. Schumacker is a Professor of Educational Research at The University of Alabama, USA, where he teaches courses in multiple regression, multivariate statistics, and structural equation modeling.

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