Multiple Regression and Beyond
eBook - ePub

Multiple Regression and Beyond

An Introduction to Multiple Regression and Structural Equation Modeling

  1. English
  2. ePUB (mobile friendly)
  3. Available on iOS & Android
eBook - ePub

Multiple Regression and Beyond

An Introduction to Multiple Regression and Structural Equation Modeling

About this book

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)

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Yes, you can access Multiple Regression and Beyond by Timothy Z. Keith,Matthew Reynolds,Jacqueline Caemmerer in PDF and/or ePUB format, as well as other popular books in Education & Social Science Research & Methodology. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover
  2. Half Title
  3. Title
  4. Copyright
  5. Contents
  6. Preface
  7. Notes for the Fourth Edition
  8. Acknowledgments
  9. Part 1 Multiple Regression
  10. Part 2 Beyond Multiple Regression: Structural Equation Modeling
  11. Appendices
  12. References
  13. Author index
  14. Subject index