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Interaction Effects in Linear and Generalized Linear Models

Interaction Effects in Linear and Generalized Linear Models
Author: Robert L. Kaufman
Publisher:
Total Pages: 584
Release: 2019
Genre: Linear models (Statistics)
ISBN: 9781506365404

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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 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.


Interaction Effects in Linear and Generalized Linear Models

Interaction Effects in Linear and Generalized Linear Models
Author: Robert L. Kaufman
Publisher: SAGE Publications
Total Pages: 609
Release: 2018-09-06
Genre: Social Science
ISBN: 1506365396

Download Interaction Effects in Linear and Generalized Linear Models Book in PDF, ePub and Kindle

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 (downloadable from the Robert L. Kaufman’s website), 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 data sets and the Stata code to reproduce the results of the application examples are available online.


Generalized Linear Mixed Models

Generalized Linear Mixed Models
Author: Walter W. Stroup
Publisher: CRC Press
Total Pages: 547
Release: 2016-04-19
Genre: Mathematics
ISBN: 1439815135

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With numerous examples using SAS PROC GLIMMIX, this text presents an introduction to linear modeling using the generalized linear mixed model as an overarching conceptual framework. For readers new to linear models, the book helps them see the big picture. It shows how linear models fit with the rest of the core statistics curriculum and points out the major issues that statistical modelers must consider.


Interpretable Machine Learning

Interpretable Machine Learning
Author: Christoph Molnar
Publisher: Lulu.com
Total Pages: 320
Release: 2020
Genre: Artificial intelligence
ISBN: 0244768528

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This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.


Beyond Multiple Linear Regression

Beyond Multiple Linear Regression
Author: Paul Roback
Publisher: CRC Press
Total Pages: 436
Release: 2021-01-14
Genre: Mathematics
ISBN: 1439885400

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Beyond Multiple Linear Regression: Applied Generalized Linear Models and Multilevel Models in R is designed for undergraduate students who have successfully completed a multiple linear regression course, helping them develop an expanded modeling toolkit that includes non-normal responses and correlated structure. Even though there is no mathematical prerequisite, the authors still introduce fairly sophisticated topics such as likelihood theory, zero-inflated Poisson, and parametric bootstrapping in an intuitive and applied manner. The case studies and exercises feature real data and real research questions; thus, most of the data in the textbook comes from collaborative research conducted by the authors and their students, or from student projects. Every chapter features a variety of conceptual exercises, guided exercises, and open-ended exercises using real data. After working through this material, students will develop an expanded toolkit and a greater appreciation for the wider world of data and statistical modeling. A solutions manual for all exercises is available to qualified instructors at the book’s website at www.routledge.com, and data sets and Rmd files for all case studies and exercises are available at the authors’ GitHub repo (https://github.com/proback/BeyondMLR)


Generalized Linear Models

Generalized Linear Models
Author: P. McCullagh
Publisher: Routledge
Total Pages: 361
Release: 2019-01-22
Genre: Mathematics
ISBN: 1351445847

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The success of the first edition of Generalized Linear Models led to the updated Second Edition, which continues to provide a definitive unified, treatment of methods for the analysis of diverse types of data. Today, it remains popular for its clarity, richness of content and direct relevance to agricultural, biological, health, engineering, and ot


Interaction Effects in Multiple Regression

Interaction Effects in Multiple Regression
Author: James Jaccard
Publisher: SAGE Publications
Total Pages: 104
Release: 2003-03-05
Genre: Social Science
ISBN: 1544332572

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Interaction Effects in Multiple Regression has provided students and researchers with a readable and practical introduction to conducting analyses of interaction effects in the context of multiple regression. The new addition will expand the coverage on the analysis of three way interactions in multiple regression analysis. Learn more about "The Little Green Book" - QASS Series! Click Here


Applying Generalized Linear Models

Applying Generalized Linear Models
Author: James K. Lindsey
Publisher: Springer Science & Business Media
Total Pages: 265
Release: 2008-01-15
Genre: Mathematics
ISBN: 038722730X

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This book describes how generalised linear modelling procedures can be used in many different fields, without becoming entangled in problems of statistical inference. The author shows the unity of many of the commonly used models and provides readers with a taste of many different areas, such as survival models, time series, and spatial analysis, and of their unity. As such, this book will appeal to applied statisticians and to scientists having a basic grounding in modern statistics. With many exercises at the end of each chapter, it will equally constitute an excellent text for teaching applied statistics students and non- statistics majors. The reader is assumed to have knowledge of basic statistical principles, whether from a Bayesian, frequentist, or direct likelihood point of view, being familiar at least with the analysis of the simpler normal linear models, regression and ANOVA.


The Oxford Handbook of Quantitative Methods in Psychology: Vol. 2

The Oxford Handbook of Quantitative Methods in Psychology: Vol. 2
Author: Todd D. Little
Publisher:
Total Pages: 785
Release: 2013-03-21
Genre: Psychology
ISBN: 0199934894

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The Oxford Handbook of Quantitative Methods in Psychology provides an accessible and comprehensive review of the current state-of-the-science and a one-stop source for learning and reviewing current best-practices in a quantitative methods across the social, behavioral, and educational sciences.