Log-Linear Modeling :Concepts, Interpretation, and Application

Publication subTitle :Concepts, Interpretation, and Application

Author: Alexander von Eye  

Publisher: John Wiley & Sons Inc‎

Publication year: 2013

E-ISBN: 9781118391747

P-ISBN(Hardback):  9781118146408

Subject: O212.4 Multivariate Analyses

Language: ENG

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Description

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.

Chapter

Cover

pp.:  1 – 5

Title Page

pp.:  5 – 6

Copyright Page

pp.:  6 – 7

CONTENTS

pp.:  7 – 13

Preface

pp.:  13 – 17

Acknowledgments

pp.:  17 – 19

2 Effects in a Table

pp.:  31 – 41

3 Goodness-of-Fit

pp.:  41 – 73

4 Hierarchical Log-linear Models and Odds Ratio Analysis

pp.:  73 – 117

5 Computations I: Basic Log-linear Modeling

pp.:  117 – 133

6 The Design Matrix Approach

pp.:  133 – 151

7 Parameter Interpretation and Significance Tests

pp.:  151 – 179

8 Computations II: Design Matrices and Poisson GLM

pp.:  179 – 203

9 Nonhierarchical and Nonstandard Log-linear Models

pp.:  203 – 273

10 Computations III: Nonstandard Models

pp.:  273 – 295

11 Sampling Schemes and Chi-square Decomposition

pp.:  295 – 311

12 Symmetry Models

pp.:  311 – 331

13 Log-linear Models of Rater Agreement

pp.:  331 – 349

14 Comparing Associations in Subtables: Homogeneity of Associations

pp.:  349 – 363

15 Logistic Regression and Logit Models

pp.:  363 – 389

16 Reduced Designs

pp.:  389 – 405

17 Computations IV: Additional Models

pp.:  405 – 443

References

pp.:  443 – 459

Topic Index

pp.:  459 – 465

Author Index

pp.:  465 – 469

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