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Interaction Effects in Linear and Generalized Linear Models: Examples and Applications Using Stata. 線形・一般化線形モデルにおける相互作用効果
・ISBN 978-1-5063-6537-4 hard GB£ 125.00
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お気に入り
★★★
| 著者・編者 | Kaufman, Robert L., |
|---|---|
| シリーズ | Advanced Quantitative Techniques in the Social Sciences Series |
| 出版社 | (Sage, UK) |
| 出版年月 | 2018 |
| ページ数 | 618 pp. |
| 言語 | ENG |
| ニュース番号 | ＜648-42 648-P71＞ |
解説
"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 (R) routines to produce the calculations, tables, and graphics for each interpretive tool discussed. Also available are the Stata (R) 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 (R) routines to produce the calculations, tables, and graphics for each interpretive tool discussed. Also available are the Stata (R) dataset files to run the examples in the book.