Multiple Regression and Beyond: An Introduction to Multiple Regression and Structural Equation Modeling

Multiple Regression and Beyond: An Introduction to Multiple Regression and Structural Equation Modeling

Companion Website materials: https://tzkeith.com/ Multiple Regression and Beyond offers a conceptually-oriented introduction to multiple regression (MR) analysis and structural equation modeling (SEM), along with analyses that flow naturally from those methods. By focusing on the concepts and purposes of MR and related methods, rather than the derivation and calculation of formulae, this book introduces material to students more clearly, and in a less threatening way. In addition to illuminating content necessary for coursework, the accessibility of this approach means students are more likely to be able to conduct research using MR or SEM–and more likely to use the methods wisely.This book:? Covers both MR and SEM, while explaining their relevance to one another? Includes path analysis, confirmatory factor analysis, and latent growth modeling? Makes extensive use of real-world research examples in the chapters and in the end-of-chapter exercises? Extensive use of figures and tables providing examples and illustrating key concepts and techniquesNew to this edition:? New chapter on mediation, moderation, and common cause? New chapter on the analysis of interactions with latent variables and multilevel SEM? Expanded coverage of advanced SEM techniques in chapters 18 through 22? International case studies and examples? Updated instructor and student online resources

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About the Author

Timothy Z. He is a professor at the University of Texas. His research focuses on the nature and measurement of intelligence, as well as the validity of tests of intelligence and theories from which they are drawn. He was awarded the senior scientist distinction by the School Psychology division of the APA for his research, which was recognized with awards from the three major journals in school psychology.

–This text refers to the paperback edition.

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#674,534 in Kindle Store (See Top 100 in Kindle Store) #248 in Education Theory Research #308 in Social Science Research #366 in Probability & Statistics (Kindle Store)

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