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

Keith, Timothy Z./ Reynolds, Matthew/ Caemmerer, Jacqueline

ISBN 10: 1032520957 / ISBN 13: 9781032520957

Published by Routledge, 2025

About this Item

4th edition. 676 pages. 10.00x7.00x10.00 inches. In Stock.

Seller Inventory # x-1032520957

Bibliographic Details

• Title: Multiple Regression and Beyond: An Introduction to Multiple Regression and Structural Equation Modeling
• Publisher: Routledge
• Publication Date: 2025
• Language: English
• ISBN 10: 1032520957
• ISBN 13: 9781032520957
• Binding: Hardcover
• Edition: 4th Edition
• Condition: Brand New
• Weight: 1.44 kilograms

About this title

Synopsis

Multiple Regression and Beyond provides a conceptually oriented introduction to multiple regression (MR) analysis and structural equation modeling (SEM), along with related analyses. By emphasizing the concepts and purposes of MR rather than the derivation and calculation of formulas, this book presents the material in a clearer and more accessible way. This approach not only covers essential coursework but also makes it more approachable for students, increasing the likelihood that they will conduct research using MR or SEM effectively and wisely.

This book covers both MR and SEM, explaining their relevance to each other. It also includes path analysis, confirmatory factor analysis, and latent growth modeling, incorporating real-world research examples throughout the chapters and end-of-chapter exercises. Figures and tables are used extensively to illustrate key concepts and techniques.

This new edition includes:

• New sections on quantile regression, statistical suppression, contrast coding, and random intercept panel models

• Support for the statistical program R and the R package lavaan in the text and on the website (www.tzkeith.com)
• New examples and exercises
• Updated instructor and student online resources (www.tzkeith.com)

About the Author

Timothy Z. Keith is Professor Emeritus at the University of Texas, Austin. Before retiring he was director of the graduate school psychology program (now school and clinical child psychology) in the Department of Educational Psychology. His research focused on the nature and measurement of intelligence, including the validity of tests of intelligence and the theories from which they are drawn.

Matthew R. Reynolds is Professor of Educational Psychology at the University of Kansas. His research focuses on the measurement and structure of human cognitive abilities and on sex differences in cognitive abilities and academic achievement.

Jacqueline M. Caemmerer is an Assistant Professor in the Department of Educational Psychology (school psychology graduate programs) at the University of Connecticut. Her research interests are in psychological assessment and validity issues. She is interested in better understanding what frequently used tests measure, their predictive validity, and developmental and cultural considerations of tests.