ABSTRACT

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 techniques

New 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

part I|254 pages

Multiple Regression

chapter 1|23 pages

Simple Bivariate Regression

chapter 2|18 pages

Multiple Regression

Introduction

chapter 3|13 pages

Multiple Regression

More Depth

chapter 5|31 pages

Three Types of Multiple Regression

chapter 6|21 pages

Analysis of Categorical Variables

chapter 9|18 pages

Mediation, Moderation, and Common Cause

chapter 10|31 pages

Multiple Regression

Summary, Assumptions, Diagnostics, Power, and Problems

chapter 11|29 pages

Related Methods

Logistic Regression and Multilevel Modeling

part II|330 pages

Beyond Multiple Regression: Structural Equation Modeling

chapter 12|24 pages

Path Modeling

Structural Equation Modeling With Measured Variables

chapter 13|15 pages

Path Analysis

Assumption and Dangers

chapter 14|38 pages

Analyzing Path Models Using SEM Programs

chapter 15|14 pages

Error

The Scourge of Research

chapter 16|41 pages

Confirmatory Factor Analysis I

chapter 17|20 pages

Putting It All Together

Introduction to Latent Variable SEM

chapter 18|35 pages

Latent Variable Models II

Multigroup Models, Panel Models, Dangers and Assumptions

chapter 19|31 pages

Latent Means in SEM

chapter 20|38 pages

Confirmatory Factor Analysis II

Invariance and Latent Means

chapter 21|21 pages

Latent Growth Models

chapter 23|24 pages

Summary

Path Analysis, CFA, SEM, Mean Structures, and Latent Growth Models