Interaction Effects in Linear and Generalized Linear Models
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Interaction Effects in Linear and Generalized Linear Models: Examples and Applic
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Quantitative methods
Regression
SN=Advanced Quantitative Techniques in the Social Sciences
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Statistics
Product details
- ISBN 9781506365374
- Weight: 1310g
- Dimensions: 177 x 254mm
- Publication Date: 06 Feb 2019
- Publisher: SAGE Publications Inc
- Publication City/Country: US
- Product Form: Hardback
- Language: English
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"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."
–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 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.
–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 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.
Robert Kaufman (PhD University of Wisconsin, 1981) is professor of sociology and the Chair of the Department of Sociology at Temple University. His substantive research focuses on economic structure and labor market inequality, especially with respect to race, ethnicity, and gender. He has also explored other realms of race-ethnic inequality, including research on wealth, home equity, residential segregation, traffic stops and treatment by police, and media portrayals of crime. More abstract statistical issues motivate some of his current work on evaluating different methods for correcting for heteroskedasticity using Monte Carlo simulations. Dr. Kaufman has published papers on quantitative methods in American Sociological Review, American Journal of Sociology, Sociological Methodology, Sociological Methods and Research, and Social Science Quarterly. He served on the editorial board of Sociological Methods and Research for 15 years and has taught graduate-level statistics courses nearly every year for the past 30 years.
