First Course in Structural Equation Modeling

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A01=George A. Marcoulides
A01=Tenko Raykov
ABSOLUTE STANDARDIZED RESIDUALS
Analyzed Covariance Matrix
Author_George A. Marcoulides
Author_Tenko Raykov
behavioral data analysis
Category=PBT
Co-variance Matrix
Command File
Control Group
Descriptive Fit Indices
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
EQS Input File
EQS Output
Experimental Group
Fit Index
FR Ly
Independence Model
introductory latent variable modeling
LISREL Input File
LISREL Notation
LS Model
Model Fit
Mplus software applications
multivariate statistics
Path Analysis Model
path analysis techniques
psychometric modeling
regression modeling
SEM Application
SR Model
Structural Equation Models
TESTING FACTORIAL INVARIANCE
Unidentified Parameter
V1 V2 V3 V4 V5
V2 V3 V4 V5
V4 V5 V6

Product details

  • ISBN 9780805855883
  • Weight: 800g
  • Dimensions: 152 x 229mm
  • Publication Date: 21 Mar 2006
  • Publisher: Taylor & Francis Inc
  • Publication City/Country: US
  • Product Form: Paperback
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In this book, authors Tenko Raykov and George A. Marcoulides introduce students to the basics of structural equation modeling (SEM) through a conceptual, nonmathematical approach. For ease of understanding, the few mathematical formulas presented are used in a conceptual or illustrative nature, rather than a computational one.

Featuring examples from EQS, LISREL, and Mplus, A First Course in Structural Equation Modeling is an excellent beginner’s guide to learning how to set up input files to fit the most commonly used types of structural equation models with these programs. The basic ideas and methods for conducting SEM are independent of any particular software.

Highlights of the Second Edition include:

• Review of latent change (growth) analysis models at an introductory level

• Coverage of the popular Mplus program

• Updated examples of LISREL and EQS

• Downloadable resources that contains all of the text’s LISREL, EQS, and Mplus examples.

A First Course in Structural Equation Modeling is intended as an introductory book for students and researchers in psychology, education, business, medicine, and other applied social, behavioral, and health sciences with limited or no previous exposure to SEM. A prerequisite of basic statistics through regression analysis is recommended. The book frequently draws parallels between SEM and regression, making this prior knowledge helpful.

Tenko Raykov (Author) ,  George A. Marcoulides (Author)

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