Interaction Effects in Logistic Regression

Interaction Effects in Logistic Regression
Author: James Jaccard
Publisher: SAGE Publications
Total Pages: 84
Release: 2001-02-21
Genre: Social Science
ISBN: 1544332599

This book provides an introduction to the analysis of interaction effects in logistic regression by focusing on the interpretation of the coefficients of interactive logistic models for a wide range of situations encountered in the research literature. The volume is oriented toward the applied researcher with a rudimentary background in multiple regression and logistic regression and does not include complex formulas that could be intimidating to the applied researcher.

Interaction Effects in Multiple Regression

Interaction Effects in Multiple Regression
Author: James Jaccard
Publisher: SAGE Publications
Total Pages: 108
Release: 2003-03-05
Genre: Social Science
ISBN: 1544332572

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.

Feature Engineering and Selection

Feature Engineering and Selection
Author: Max Kuhn
Publisher: CRC Press
Total Pages: 266
Release: 2019-07-25
Genre: Business & Economics
ISBN: 1351609467

The process of developing predictive models includes many stages. Most resources focus on the modeling algorithms but neglect other critical aspects of the modeling process. This book describes techniques for finding the best representations of predictors for modeling and for nding the best subset of predictors for improving model performance. A variety of example data sets are used to illustrate the techniques along with R programs for reproducing the results.

Applied Logistic Regression Analysis

Applied Logistic Regression Analysis
Author: Scott Menard
Publisher: SAGE
Total Pages: 130
Release: 2002
Genre: Mathematics
ISBN: 9780761922087

The focus in this Second Edition is again on logistic regression models for individual level data, but aggregate or grouped data are also considered. The book includes detailed discussions of goodness of fit, indices of predictive efficiency, and standardized logistic regression coefficients, and examples using SAS and SPSS are included. More detailed consideration of grouped as opposed to case-wise data throughout the book Updated discussion of the properties and appropriate use of goodness of fit measures, R-square analogues, and indices of predictive efficiency Discussion of the misuse of odds ratios to represent risk ratios, and of over-dispersion and under-dispersion for grouped data Updated coverage of unordered and ordered polytomous logistic regression models.

Interpretable Machine Learning

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

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.

Multiple Regression

Multiple Regression
Author: Leona S. Aiken
Publisher: SAGE
Total Pages: 228
Release: 1991
Genre: Business & Economics
ISBN: 9780761907121

This successful book, now available in paperback, provides academics and researchers with a clear set of prescriptions for estimating, testing and probing interactions in regression models. Including the latest research in the area, such as Fuller's work on the corrected/constrained estimator, the book is appropriate for anyone who uses multiple regression to estimate models, or for those enrolled in courses on multivariate statistics.

Interaction Effects in Logistic Regression

Interaction Effects in Logistic Regression
Author: James Jaccard
Publisher: SAGE
Total Pages: 84
Release: 2001-02-21
Genre: Mathematics
ISBN: 9780761922070

This book provides an introduction to the analysis of interaction effects in logistic regression by focusing on the interpretation of the coefficients of interactive logistic models for a wide range of situations encountered in the research literature. The volume is oriented toward the applied researcher with a rudimentary background in multiple regression and logistic regression and does not include complex formulas that could be intimidating to the applied researcher.Learn more about "The Little Green Book" - QASS Series! Click Here

Practical Guide to Logistic Regression

Practical Guide to Logistic Regression
Author: Joseph M. Hilbe
Publisher: CRC Press
Total Pages: 170
Release: 2016-04-05
Genre: Mathematics
ISBN: 1498709583

Practical Guide to Logistic Regression covers the key points of the basic logistic regression model and illustrates how to use it properly to model a binary response variable. This powerful methodology can be used to analyze data from various fields, including medical and health outcomes research, business analytics and data science, ecology, fishe

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: 427
Release: 2018-09-06
Genre: Social Science
ISBN: 1506365361

"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.