These four volumes provide a collection of key publications on categorical data analysis, carefully put together so that the reader can easily navigate, understand and put in context the major concepts and methods of analysing categorical data. The major work opens with a series of papers that address general issues in CDA, and progresses with publications which follow a logical movement from the statistics for analysing a single categorical variable, to those for studying the relationships between two and more categorical variables, and to categorical variables in some of more advanced methods, such as latent class analysis. Edited and introduced by a leading voice in the field, this collection helpfully includes both theoretical and applied items on its theme, in order to help the reader understand the methods and use them in empirical research.
Volume 1: Basic Concepts and Principles
Volume 2: Statistical Methods for Analysing Associations
Volume 3: Log-Linear and Logistic Regression Models
Volume 4: Advanced and Graphical Statistical Methods
VOLUME ONE: BASIC CONCEPTS AND PRINCIPLES
Introduction
Part One: Overview of Categorical Data Analysis
Statistical Magic and/or Statistical Serendipity: An Age of Progress in
the Analysis of Categorical Data - Leo Goodman
Categorical Data Analysis - Thomas Wickens
Part Two: Statistical Methods and Graphs for One Categorical Variable
On the Theory of Scales of Measurement - S. Stevens
Statistical Analysis of Qualitative Variation - Alan Agresti and Barbara
Agresti
No Humble Pie: The Origins and Usage of a Statistical Chart - Ian Spence
Bah! Bar Charts - Allan Reese
Revising the Pareto Chart - Leland Wilkinson
Part Three: The Chi-Square Test
Karl Pearson and the Chi-Squared Test - R. Plackett
The Use of Chi-Squared Statistics for Categorical Data Problems - Stephen
Fienberg
Sample Size Restraints Commonly Imposed on the Use of the Chi-Square
Statistic - John Roscoe and Jackson Byars
What Is the Continuity Correction? - Nathan Mantel and Samuel Greenhouse
Some Reasons for Not Using the Yates Continuity Correction on 2 ×2
Contingency Tables: Comment and a Suggestion - Nathan Mantel
Part Four: Exact Inference for Contingency Tables
On the Interpretation of ?2 from Contingency Tables, and the Calculation
of P - R. Fisher
Fishers Exact Test - Graham Upton
A Survey of Exact Inference for Contingency Tables - Alan Agesti
Part Five: Measuring the Relationship between Two Ordinal Variables
On the Association of Attributes in Statistics: With Illustrations from
the Material of the Childhood Society, &c - G. Udny Yule
A New Measure of Rank Correlation - M. Kendall
The Treatment of Ties in Ranking Problems - M. Kendall
A New Asymmetric Measure of Association for Ordinal Variables - Robert
Somers
VOLUME TWO: STATISTICAL METHODS FOR ANALYSING ASSOCIATIONS
Part One: Simpsons Paradox
Simpsons Paradox in Real Life - Clifford Wagner
Minority Contributions to the SAT Score Turnaround: An Example of
Simpsons Paradox - Howard Wainer
Confounding and Collapsibility in Causal Inference - Sander Greenland,
James Robins and Judea Pearl
Part Two: Mobility Tables
Status, Autonomy, and Training in Occupational Mobility - Michael Hout
A New Index of Structure for the Analysis of Models for Mobility Tables
and Other Cross-Classifications - Clifford Clogg, Tamas Rudas and Liwen Xi
Part Three: Statistical Tests for High Dimensional Tables
Preliminary Graphical Analysis and Quasi-Independence for a Two-Way
Contingency Table - Stephen Fienberg
The Analysis of Multidimensional Contingency Tables - Stephen Fienberg
The Analysis of Incomplete Multi-Way Contingency Tables - Stephen
Fienberg
Partitioning of Chi-Square, Analysis of Marginal Contingency Tables, and
Estimation of Expected Frequencies in Multidimensional Contingency Tables -
Leo Goodman
Part Four: Association Models
Simple Models for the Analysis of Association in Cross-Classifications
Having Ordered Categories - Leo Goodman
Analysis of Sets of Two-Way Contingency Tables Using Association Models -
Mark Becker and Clifford Clogg
A Survey of Strategies for Modeling Cross-Classifications Having Ordinal
Variables - Alan Agresti
Part Five: Dealing with Sparseness
Methods for the Analysis of Contingency Tables with Large and Small Cell
Counts - Jenny Baglivo, Donald Oliver and Marcello Pagano
Goodness-of-Fit Tests for Loglinear Models in Sparse Contingency Tables -
Kenneth Koehler
VOLUME THREE: LOG-LINEAR AND LOGISTIC REGRESSION MODELS
Part One: Generalized Linear Models
Generalized Linear Models - J. Nelder and R. Wedderburn
Part Two: Log-Linear Models
An Introduction to Categorical Data Analysis - Douglas Sloane and S.
Phillip Morgan
Some Common Problems in Log-Linear Analysis - Clifford Clogg and Scott
Eliason
Part Three: Logistic Regression Models
The Regression Analysis of Binary Sequences - D. Cox
A Logistic Model for Paired Comparisons with Ordered Categorical Data - P.
McCullagh
Graphical Methods for Assessing Logistic Regression Models - James
Landwehr, Daryl Pregibon and Anne Shoemaker
Evaluating Logistic Models for Large Contingency Tables - Edward Fowlkes,
Anne Freeny and James Landwehr
A Graphical Method for Assessing the Fit of a Logistic Regression Model -
Iain Pardoe and R. Dennis Cook
Part Four: Multilevel Statistical Models for Categorical Response Variables
The Intraclass Correlation Coefficient: Distribution-Free Definition and
Test - Daniel Commenges and Helene Jacqmin
Modeling Clustered Ordered Categorical Data - Alan Agresti and Ranjini
Natarajan
Religious Attendance in Cross-National Perspective: A Multilevel Analysis
of 60 Countries - Stijn Ruiter and Frank van Tubergen
Part Five: Longitudinal Analysis for Categorical Response Variables
Longitudinal Data Analysis Using Generalized Linear Models - King-Yee
Liang and Scott Zeger
A Bayesian Hierarchical Model for Categorical Longitudinal Data from a
Social Survey of Immigrants - A. Pettitt et al.
VOLUME FOUR: ADVANCED AND GRAPHICAL STATISTICAL METHODS
Part One: Correspondence Analysis
Simple Correspondence Analysis: A Bibliographic Review - Eric Beh
Some Useful Extensions of the Usual Correspondence Analysis Approach and
the Usual Log-Linear Models Approach in the Analysis of Contingency Tables -
Leo Goodman
Part Two: Factor Analysis for Categorical Variables
Multiway Contingency Analysis with a Scaled Response or Factor - Otis
Duncan and James McRae, Jr
Factor Analysis for Categorical Data - D.J. Bartholomew
Part Three: Latent Class Models
Exploratory Latent Structure Analysis Using Both Identifiable and
Unidentifiable Models - Leo Goodman
Categorical Causal Modelling: Latent Class Analysis and Directed
Log-Linear Models with Latent Variables - Jacques Hagenaars
On the Assignment of Individuals to Latent Classes - Leo Goodman
Part Four: Missing Values in Categorical Data
Loglinear Models with Missing Data: A Latent Class Approach - Christopher
Winship and Robert Mare
Multiple Imputation of Incomplete Categorical Data Using Latent Class
Analysis - Jeroen Vermunt et al.
Part Five: Graphical Methods
Conceptual and Visual Models for Categorical Data - Michael Friendly
Mosaic Displays for Multi-Way Contingency Tables - Michael Friendly
Extending Mosaic Displays: Marginal, Conditional, and Partial Views of
Categorical Data - Michael Friendly
Multigraph Representations of Hierarchical Loglinear Models - Terry McKee
and Harry Khamis
Latent Class Factor and Cluster Models, Bi-Plots, and Related Graphical
Displays - Jay Magidson and Jeroen Vermunt
Dr Keming Yang is currently an Associate Professor of Sociology at University of Durham in the UK. He was born and grew up in the city of Tianjin, Peoples Republic of China. He studied sociology at Nankai University and worked there for three years before going to study for a PhD at Columbia University in the US. His first job after receiving the PhD was at National University of Singapore. He then took a position at University of Reading in the UK and moved to the current position at Durham. His first research area is the political and economic sociology of entrepreneurship in China, in which he published two books, Entrepreneurship in China and Capitalists in Communist China, and some articles. Since working at University of Durham, he has been working on the issue of loneliness from a sociological perspective. He is the author of Loneliness: A Social Problem and many articles on this topic. He also has research interest in research methods in the social sciences, and he is the author of Making Sense of Statistics in Social Research and the editor of Categorical Data Analysis.
