Log-Linear Models and Logistic Regression by Ronald Christensen

Log-Linear Models and Logistic Regression by Ronald Christensen

This book examines statistical models for frequency data.  The primary focus is on log-linear models for contingency tables but also includes extensive discussion of logistic regression.  Topics such as logistic discrimination, generalized linear models, and correspondence analysis are also explored.

The treatment is designed for readers with prior knowledge of analysis of variance and regression.  It builds upon the relationships between these basic models for continuous data and the analogous log-linear and logistic regression models for discrete data.  While emphasizing similarities between methods for discrete and continuous data, this book also carefully examines the differences in model interpretations and evaluation that occur due to the discrete nature of the data.  Numerous data sets from fields as diverse as engineering, education, sociology, and medicine are used to illustrate procedures and provide exercises.  A major addition to the third edition is the availability of a companion online manual providing R code for the procedures illustrated in the book.

The book begins with an extensive discussion of odds and odds ratios as well as concrete illustrations of basic independence models for contingency tables.  After developing a sound applied and theoretical basis for frequency models analogous to ANOVA and regression, the book presents, for contingency tables, detailed discussions of the use of graphical models, of model selection procedures, and of models with quantitative factors.  It then explores generalized linear models, after which all the fundamental results are reexamined using powerful matrix methods.  The book then gives an extensive treatment of Bayesian procedures for analyzing logistic regression and other regression models for binomial data.  Bayesian methods are conceptually simple and unlike traditional methods allow accurate conclusions to be drawn without requiring large sample sizes.  The book concludes with two new chapters: one on exact conditional tests for small sample sizes and another on the graphical procedure known as correspondence analysis.

Ronald Christensen is a Professor of Statistics at the University of New Mexico, Fellow of the American Statistical Association (ASA) and the Institute of Mathematical Statistics, former Chair of the ASA Section on Bayesian Statistical Science and former Editor of The American Statistician. His book publications include Plane Answers to Complex Questions (Springer 2011), Log-Linear Models and Logistic Regression (Springer 1997), Analysis of Variance, Design, and Regression (1996, 2016), and Bayesian Ideas and Data Analysis (2010, with Johnson, Branscum and Hanson).

SKU	Unavailable
ISBN 13	9783031690372
ISBN 10	3031690370
Title	Log-Linear Models and Logistic Regression
Author	Ronald Christensen
Series	Springer Texts In Statistics
Condition	Unavailable
Binding Type	Hardback
Publisher	Springer International Publishing AG
Year published	2025-04-18
Number of pages	545
Cover note	Book picture is for illustrative purposes only, actual binding, cover or edition may vary.