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Social scientists study complex phenomena about which they often propose intricate hypotheses tested with linear-interactive or multiplicative terms. While interaction terms are hardly new to social science research, researchers have yet to develop a common methodology for using and interpreting them. Modeling and Interpreting Interactive Hypotheses in Regression Analysis provides step-by-step guidance on how to connect substantive theories to statistical models and how to interpret and present the results.

"Kam and Franzese is a must-have for all empirical social scientists interested in teasing out the complexities of their data."
---Janet M. Box-Steffensmeier, Ohio State University

"Kam and Franzese have written what will become the definitive source on dealing with interaction terms and testing interactive hypotheses. It will serve as the standard reference for political scientists and will be one of those books that everyone will turn to when helping our students or doing our work. But more than that, this book is the best text I have seen for getting students to really think about the importance of careful specification and testing of their hypotheses."
---David A. M. Peterson, Texas A&M University

"Kam and Franzese have given scholars and teachers of regression models something they've needed for years: a clear, concise guide to understanding multiplicative interactions. Motivated by real substantive examples and packed with valuable examples and graphs, their book belongs on the shelf of every working social scientist."
---Christopher Zorn, University of South Carolina

"Kam and Franzese make it easy to model what good researchers have known for a long time: many important and interesting causal effects depend on the presence of other conditions. Their book shows how to explore interactive hypotheses in your own research and how to present your results. The book is straightforward yet technically sophisticated. There are no more excuses for misunderstanding, misrepresenting, or simply missing out on interaction effects!"
---Andrew Gould, University of Notre Dame

Cindy D. Kam is Assistant Professor, Department of Political Science, University of California, Davis.

Robert J. Franzese Jr. is Associate Professor, Department of Political Science, University of Michigan, and Research Associate Professor, Center for Political Studies, Institute for Social Research, University of Michigan.

For datasets, syntax, and worksheets to help readers work through the examples covered in the book, visit: www.press.umich.edu/KamFranzese/Interactions.html

Cindy D. Kam is Assistant Professor of Political Science at the University of California, Davis. 
Robert J. Franzese, Jr. is Associate Professor of Political Science at the University of Michigan and Research Associate Professor in the Center for Political Studies at the Institute for Social Research.

There's probably no better way to learn statistics than working with the data hands-on.

To that end, we have provided the following datasets, syntax, and worksheets to help our readers work through the examples we cover in the book.

All calculations, tables, and figures can be replicated by downloading each of the following Stata datasets, Stata syntax file, and Excel file (or by downloading them all in zipped form, below):


Stata code for all tables

Excel workbook for all figures*

Zipped file containing all six of the above files

If you are using Internet Explorer, this file will not download correctly by just clicking it. To download the file properly, right-click on the link and select "Save target as..." When you save the file, be sure to give it a ".xls" extension.