The Leading eBooks Store Online 4,034,055 members ⚫ 1,328,001 ebooks

New to

Learn more

Log-Linear Modeling

Concepts, Interpretation, and Application

Log-Linear Modeling by Alexander von Eye
Buy this eBook
US$ 132.00 US$ 118.80
(If any tax is payable it will be calculated and shown at checkout.)

An easily accessible introduction to log-linear modeling for non-statisticians

Highlighting advances that have lent to the topic's distinct, coherent methodology over the past decade, Log-Linear Modeling: Concepts, Interpretation, and Application provides an essential, introductory treatment of the subject, featuring many new and advanced log-linear methods, models, and applications.

The book begins with basic coverage of categorical data, and goes on to describe the basics of hierarchical log-linear models as well as decomposing effects in cross-classifications and goodness-of-fit tests. Additional topics include:

  • The generalized linear model (GLM) along with popular methods of coding such as effect coding and dummy coding
  • Parameter interpretation and how to ensure that the parameters reflect the hypotheses being studied
  • Symmetry, rater agreement, homogeneity of association, logistic regression, and reduced designs models

Throughout the book, real-world data illustrate the application of models and understanding of the related results. In addition, each chapter utilizes R, SYSTAT®, and §¤EM software, providing readers with an understanding of these programs in the context of hierarchical log-linear modeling.

Log-Linear Modeling is an excellent book for courses on categorical data analysis at the upper-undergraduate and graduate levels. It also serves as an excellent reference for applied researchers in virtually any area of study, from medicine and statistics to the social sciences, who analyze empirical data in their everyday work.

Wiley; January 2013
464 pages; ISBN 9781118391761
Read online, or download in secure EPUB or secure PDF format
Title: Log-Linear Modeling
Author: Alexander von Eye; Eun-Young Mun
  • News
  • Contents
No entry found