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Interaction Effects in Multiple Regression
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Interaction Effects in Multiple Regression

Second Edition
Volume: 72
March 2003 | 104 pages | SAGE Publications, Inc
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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 addition will expand the coverage on the analysis of three way interactions in multiple regression analysis.


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Series Editor's Introduction
 
Preface
 
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

 
Multicollinearity

 
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

 
Summary

 
 
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

 
Summary

 
 
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

 
Transformations

 
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

 
Covariates

 
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

 
 
References
 
Notes
 
About the Authors

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