Interaction Effects in Multiple Regression (Quantitative Applications in the Social Sciences)
by James Jaccard, Robert Turrisi
Interaction Effects in Multiple Regression, from the Quantitative Applications in the Social Sciences series by James Jaccard and Robert Turrisi, delves into the role of interaction terms in regression models. It equips social scientists with essential tools for analyzing complex relationships in data, promoting precise and insightful research outcomes.
About This Book
Interaction Effects in Multiple Regression is part of the Quantitative Applications in the Social Sciences series. Authored by James Jaccard and Robert Turrisi, it focuses on the principles and applications of interaction effects within multiple regression frameworks.
The book addresses how interaction terms influence the interpretation of regression models, offering insights valuable for social science research. It emphasizes practical approaches to modeling and analyzing data where variables interact.
Designed for researchers and students, the text supports the integration of advanced statistical techniques into empirical studies across various social science disciplines.
Through its concise format, the book aids in understanding the nuances of regression analysis, ensuring accurate and robust statistical conclusions.
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