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Categorical Data Analysis

Categorical Data Analysis

Four Volume Set
Edited by:

June 2014 | 1 376 pages | SAGE Publications Ltd

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

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
Fisher’s 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
Part One: Simpson’s Paradox
Simpson’s Paradox in Real Life

Clifford Wagner
Minority Contributions to the SAT Score Turnaround: An Example of Simpson's 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
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.
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

Keming Yang

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, People’s 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... More About Author