Although factorial analysis is widely used in the social sciences, there is some confusion as to how to use the technique's most powerful feature - the evaluation of interaction effects. Written to remedy this situation, this book explores the issues underlying the effective analysis of interaction in factorial designs.The author begins by describing different ways of characterizing interactions in ANOVA, elucidating both moderator conceptualizations of interactions as well as that of residualized means. After discussing interaction effects using traditional hypothesis testing approaches, it then covers alternative analytic frameworks that focus on effect size methodology and interval estimation. Jaccard summarizes criticisms of classical null hypothesis testing and offers practical guidelines for pursuing magnitude estimation and interval estimation approaches.
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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 interaction effects in a wide range of statistical models and teaches advanced graduate courses on structural equation modeling. He has written influential articles on the issue of arbitrary metrics in social science research. Dr. Jaccard also has written about theory construction and how to build conceptual models in a book published by Guilford Press.
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book explores the issues underlying the effective analysis of interaction in factorial designs. It includes discussion of: different ways of characterizing interactions in ANOVA interaction effects using traditional hypothesis testing approaches and . Nº de ref. del artículo: 594967179
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