You are here

Interaction Effects in Multiple Regression

Interaction Effects in Multiple Regression

Second Edition

March 2003 | 104 pages | SAGE Publications, Inc
Interaction Effects in Multiple Regression has provided students and researchers with a readable and practical introduction to conducting analyses of interaction effects in the context of multiple regression. The new Second Edition will expand the coverage on the analysis of three-way interactions in multiple regression analysis.
Series Editor's Introduction
Chapter 1: Introduction
The Concept of Interaction

Simple Effects and Interaction Contrasts

Simple Effects

Interaction Contrasts

A Review of Multiple Regression

The Linear Model

Hierarchical Regression

Categorical Predictors and Dummy Variables

Predicted Values in Multiple Regression

Transformations of the Predictor Variables

Overview of Book

Chapter 2: Two-Way Interactions
Regression Models with Product Terms

Two Continuous Predictors

The Traditional Regression Strategy

The Form of the Interaction

Interpreting the Regression Coefficients for the Product Term

Interpreting the Regression Coefficients for the Component Terms

Significance Tests and Confidence Intervals


Strength of the Interaction Effect

A Numerical Example

Graphical Presentation

A Qualitative Predictor and a Continuous Predictor

A Qualitative Moderator Variable

A Continuous Moderator Variable

More Than Two Groups for the Qualitative Variable

Form of the Interaction


Chapter 3: Three-Way Interactions
Three Continuous Predictors

Qualitative and Continuous Predictors

A Continuous Focal Independent Variable

A Qualitative Focal Independent Variable

Qualitative Variables with More than Two Levels


Chapter 4: Additional Considerations
Selected Issues

The BiLinear Nature of Interactions for Continuous Variables

Calculating Coefficients of Focal Independent Variables at Different Moderator Values

Partialing the Component Terms


Multiple Interaction Effects

Standardized and Unstandardized Coefficients

Metric Properties

Measurement Error

Robust Analyses and Assumption Violations

Within-Subject and Repeated-Measure Designs

Ordinal and Disordinal Interactions

Regions of Significance

Confounded Interactions

Optimal Experimental Designs and Statistical Power


Control for Experimentwise Errors

Omnibus Tests and Interaction Effects

Some Common Misapplications

Interaction Models with Clustered Data and Random Coefficient Models

Continuous Versus Discrete Predictor Variables

The Moderator Framework Revisited

About the Authors

James Jaccard

Dr. James Jaccard is Professor of Social Work at New York University Silver School of Social Work. He received his doctoral degree from the University of Illinois, Urbana, in 1976. Dr. Jaccard’s research focuses on adolescent and young adult problem behaviors, particularly those related to unintended pregnancy and substance use, broadly defined. He has developed parent-based interventions to teach parents how to more effectively communicate and parent their adolescent children so as to reduce the risk of unintended pregnancies and problems due to substance use. Dr. Jaccard has written numerous books and articles on the analysis of... More About Author

Robert Turrisi

Purchasing options

Please select a format:

ISBN: 9780761927426

SAGE Research Methods is a research methods tool created to help researchers, faculty and students with their research projects. SAGE Research Methods links over 175,000 pages of SAGE’s renowned book, journal and reference content with truly advanced search and discovery tools. Researchers can explore methods concepts to help them design research projects, understand particular methods or identify a new method, conduct their research, and write up their findings. Since SAGE Research Methods focuses on methodology rather than disciplines, it can be used across the social sciences, health sciences, and more.