The book "A First Course in Structural Equation Modeling" by Tenko Raykov and George A. Marcoulides is an introductory text designed for advanced undergraduate and graduate students, as well as researchers from various disciplines. The second edition aims to provide a current and updated conceptual and nonmathematical introduction to structural equation modeling (SEM) in the social and behavioral sciences. The authors emphasize that the book is suitable for readers with limited or no prior exposure to SEM, focusing on the fundamental aspects of SEM rather than advanced topics. The book covers the basics of SEM, including the structure of input files for SEM programs (EQS, LISREL, and Mplus), and provides an overview of path analysis, confirmatory factor analysis, structural regression models, and latent change analysis. It also discusses the importance of SEM in handling measurement errors, developing and testing theories, and studying longitudinal data. Key features of SEM models include their ability to model latent variables, account for measurement errors, and fit to covariance or correlation matrices. The book illustrates these concepts using examples from each of the three software programs: EQS, LISREL, and Mplus. While the book does not cover every aspect of SEM, it serves as a foundational resource for beginners, with more advanced topics available in other specialized texts. The authors acknowledge the contributions of several scholars and colleagues who have influenced their understanding of SEM and provided valuable feedback on earlier drafts. The book is published by Lawrence Erlbaum Associates and is intended to be a stand-alone precursor to more advanced SEM texts.The book "A First Course in Structural Equation Modeling" by Tenko Raykov and George A. Marcoulides is an introductory text designed for advanced undergraduate and graduate students, as well as researchers from various disciplines. The second edition aims to provide a current and updated conceptual and nonmathematical introduction to structural equation modeling (SEM) in the social and behavioral sciences. The authors emphasize that the book is suitable for readers with limited or no prior exposure to SEM, focusing on the fundamental aspects of SEM rather than advanced topics. The book covers the basics of SEM, including the structure of input files for SEM programs (EQS, LISREL, and Mplus), and provides an overview of path analysis, confirmatory factor analysis, structural regression models, and latent change analysis. It also discusses the importance of SEM in handling measurement errors, developing and testing theories, and studying longitudinal data. Key features of SEM models include their ability to model latent variables, account for measurement errors, and fit to covariance or correlation matrices. The book illustrates these concepts using examples from each of the three software programs: EQS, LISREL, and Mplus. While the book does not cover every aspect of SEM, it serves as a foundational resource for beginners, with more advanced topics available in other specialized texts. The authors acknowledge the contributions of several scholars and colleagues who have influenced their understanding of SEM and provided valuable feedback on earlier drafts. The book is published by Lawrence Erlbaum Associates and is intended to be a stand-alone precursor to more advanced SEM texts.