Leona S. Aiken, Stephen G. West

Multiple Regression: Testing and Interpreting Interactions

Broschiertes Buch

Produktbeschreibung

This successful book, now available in paperback, provides academics and researchers with a clear set of prescriptions for estimating, testing and probing interactions in regression models. Including the latest research in the area, such as Fuller's work on the corrected/constrained estimator, the book is appropriate for anyone who uses multiple regression to estimate models, or for those enrolled in courses on multivariate statistics.

Produktdetails

• Verlag: SAGE PUBN
• Seitenzahl: 224
• Erscheinungstermin: Januar 1991
• Englisch
• Abmessung: 217mm x 141mm x 14mm
• Gewicht: 300g
• ISBN-13: 9780761907121
• ISBN-10: 0761907122
• Artikelnr.: 21962313

Autorenporträt

Leona S. Aiken (PhD, Purdue University) is Professor and Chair of Social and Quantitative Psychology at Arizona State University. Her research interests include both quantitative methods and health psychology. In quantitative methods, she is known for her work in continuous variable interactions in multiple regression. She is also interested in the use of design approaches and mediational analysis to untangle the effects of individual components in multi-component interventions. In health psychology, she is interested in adoption of health protective behaviors across the life span, particularly among women, both from the perspectives of psychosocial models of the putative determinants of health protective behavior and from the perspective of interventions to increase health protective behavior.

Inhaltsangabe

Introduction
Interactions between Continuous Predictors in Multiple Regression
The Effects of Predictor Scaling on Coefficients of Regression Equations
Testing and Probing Three-Way Interactions
Structuring Regression Equations to Reflect Higher Order Relationships
Model and Effect Testing with Higher Order Terms
Interactions between Categorical and Continuous Variables
Reliability and Statistical Power
Conclusion
Some Contrasts Between ANOVA and MR in Practice