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Interaction effects in multiple regression / James Jaccard, Robert Turrisi.

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LIBRA HA31.3 .J33 2003
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Format:
Book
Author/Creator:
Jaccard, James.
Contributor:
Turrisi, Robert.
Series:
Quantitative applications in the social sciences ; no. 07-072.
Sage university papers series. Quantitative applications in the social sciences ; no. 07-72
Language:
English
Subjects (All):
Regression analysis.
Social sciences--Statistical methods.
Social sciences.
Regressieanalyse.
Regression Analysis.
Social Sciences.
Medical Subjects:
Regression Analysis.
Social Sciences.
Local Subjects:
Regressieanalyse.
Physical Description:
vii, 92 pages : illustrations ; 22 cm.
Edition:
Second edition.
Place of Publication:
Thousand Oaks, Calif. : Sage Publications, [2003]
Summary:
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. Contents: About the Author/Preface/Introduction/Two Way Interactions/Three Way Interactions/Additional Considerations/References
Contents:
1. Introduction
The concept of interaction
Simple effects and interaction contrasts
A review of multiple regression
Overview of book
2. Two-way interactions
Regression models with product terms
Two continuous predictors
A qualitative predictor and a continuous predictor
Summary
3. Three-way interactions
Three continuous predictors
Qualitative and continuous predictors
4. Additional considerations
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 error
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.
Notes:
Includes bibliographical references (pages 89-91) and index.
Other Format:
Online version: Jaccard, James. Interaction effects in multiple regression.
ISBN:
0761927425
9780761927426
OCLC:
50942108
Publisher Number:
9780761927426

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