Interaction Effects in Logistic Regression

Author: James Jaccard
Publisher: SAGE Publications
ISBN: 1544332599
Category : Social Science
Languages : en
Pages : 84

Book Description
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

Author: James Jaccard
Publisher: SAGE Publications
ISBN: 1544332572
Category : Social Science
Languages : en
Pages : 108

Book Description
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

Author: Max Kuhn
Publisher: CRC Press
ISBN: 1351609467
Category : Business & Economics
Languages : en
Pages : 266

Book Description
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

Author: Scott Menard
Publisher: SAGE
ISBN: 9780761922087
Category : Mathematics
Languages : en
Pages : 130

Book Description
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

Author: Christoph Molnar
Publisher: Lulu.com
ISBN: 0244768528
Category : Computers
Languages : en
Pages : 320

Book Description
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

Author: Leona S. Aiken
Publisher: SAGE
ISBN: 9780761907121
Category : Business & Economics
Languages : en
Pages : 228

Book Description
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

Author: James Jaccard
Publisher: SAGE
ISBN: 9780761922070
Category : Mathematics
Languages : en
Pages : 84

Practical Guide to Logistic Regression

Author: Joseph M. Hilbe
Publisher: CRC Press
ISBN: 1498709583
Category : Mathematics
Languages : en
Pages : 170

Book Description
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

Author: Robert L. Kaufman
Publisher: SAGE Publications
ISBN: 1506365361
Category : Social Science
Languages : en
Pages : 427

Book Description
"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.

Regression & Linear Modeling

Author: Jason W. Osborne
Publisher: SAGE Publications
ISBN: 1506302750
Category : Psychology
Languages : en
Pages : 489

Book Description
In a conversational tone, Regression & Linear Modeling provides conceptual, user-friendly coverage of the generalized linear model (GLM). Readers will become familiar with applications of ordinary least squares (OLS) regression, binary and multinomial logistic regression, ordinal regression, Poisson regression, and loglinear models. Author Jason W. Osborne returns to certain themes throughout the text, such as testing assumptions, examining data quality, and, where appropriate, nonlinear and non-additive effects modeled within different types of linear models.