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Interaction Effects in Linear and Generalized Linear Models
Examples and Applications Using Stata

- Robert L. Kaufman - Temple University, USA

**Courses:**

Intermediate/Advanced Statistics | Multivariate Research Methods | Quantitative Methods | Regression & Correlation | Regression & Correlation | Research Methods in Sociology | Statistics in Political Science | Statistics in Political Science | Statistics in Psychology | Statistics in Sociology

–Nicole Kalaf-Hughes,

*Bowling Green State University*

Offering a clear set of workable examples with data and explanations,

**Interaction Effects in Linear and Generalized Linear Models**is a comprehensive and accessible text that provides a unified approach to interpreting interaction effects. The book develops the statistical basis for the general principles of interpretive tools and applies them to a variety of examples, introduces the ICALC Toolkit for Stata, and offers a series of start-to-finish application examples to show students how to interpret interaction effects for a variety of different techniques of analysis, beginning with OLS regression.

The author’s website at www.icalcrlk.com provides a downloadable toolkit of Stata® routines to produce the calculations, tables, and graphics for each interpretive tool discussed. Also available are the Stata® dataset files to run the examples in the book.

Coming March 29 – 30th at Temple University – Robert L. Kaufman’s workshop on Using ICALC to Interpret Interaction Effects in Linear &

Generalized Linear Models. Learn more about registration, the workshop topics and schedule here.

“This book is remarkable in its accessible treatment of interaction effects. Although this concept can be challenging for students (even those with some background in statistics), this book presents the material in a very accessible manner, with plenty of examples to help the reader understand how to interpret their results.”

**Bowling Green State University**

**“Interaction Effects in Linear and Generalized Linear Models** provides an intuitive approach that benefits both new users of Stata getting acquainted with these statistical models as well as experienced students looking for a refresher. The topic of interactions is greatly important given that many of our main theories in the social and behavioral sciences rely on moderating effects of variables. This book does a terrific job of guiding the reader through the various statistical commands available in Stata and explaining the results and taking the reader through different considerations in graphically presenting their results.”

**University of Houston**

### Sample Materials & Chapters

Chapter 1: Introduction and Background

Chapter 7: Linear Regression Model Applications