Interaction Effects in Logistic Regression (Quantitative Applications in the

Description: This book provides an introduction to the analysis of interaction effects in logistic regression by focusing on the interpretation of the coefficients of interactive logistic models for a wide range of situations encountered in the research literature. The volume is oriented toward the applied researcher with a rudimentary background in multiple regression and logistic regression and does not include complex formulas that could be intimidating to the applied researcher. James Jaccard is currently Professor of Social Work; Associate Dean for Research; Co-director, Center for Latino Adolescent and Family Health in the NYU Silver School of Social Work. He received his doctoral degree from the University of Illinois in 1976 and is the director of the Institute for Child Health and Development at Florida International University in Miami. He previously was a distinguished research professor at the State University of New York in Albany, where he was in both the department of psychology and the School of Social Welfare. Dr. Jaccard was trained as a social-developmental scientist with specialties in attitude change and decision making, particularly as applied to young adolescents. Dr. Jaccard's research focuses on adolescent problem behaviors related to unintended pregnancy and substance use. He has developed programs for parents of adolescents to teach parents how to more effectively communicate and parent their children so as to reduce the risk of unintended pregnancies and problems due to substance use. He was involved in the seminal work on the influential Theory of Reasoned Action and has developed several effective parent-based interventions to prevent adolescent risk behaviors. Dr. Jaccard was one of the designers of the National Longitudinal Study of Adolescent Health (Add Health), which interviewed over 20,000 adolescents and their mothers in a multi-wave wave panel design. Add Health is one of the largest and most influential secondary data bases on adolescent health in the United States. Dr. Jaccard also has an extensive background in psychometrics and statistical methods. He 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 is currently developing a general framework for statistical analysis that eschews p values and focuses instead on magnitude estimation and margins of error. He in on the editorial board of the Journal of the Society for Social Work and reviews quantitative applications to social work research for the journal. Finally, Dr. Jaccard has written about theory construction and how to build conceptual models. He recently completed a book with Professor Jacob Jacoby that gives social scientists practical, hands-on approaches for generating ideas and translating them into coherent theories. Introduction Interactions between Qualitative Predictors Interactions between Qualitative and Quantitative/Continuous Predictors Interactions between Quantitative/Continuous Predictors Multicategory Models Additional Considerations

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