Categorical Data Analysis

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 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.

• VOLUME ONE: BASIC CONCEPTS AND PRINCIPLESIntroductionPart One: Overview of Categorical Data AnalysisStatistical Magic and/or Statistical Serendipity: An Age of Progress in the Analysis of Categorical Data - Leo GoodmanCategorical Data Analysis - Thomas WickensPart Two: Statistical Methods and Graphs for One Categorical VariableOn the Theory of Scales of Measurement - S. StevensStatistical Analysis of Qualitative Variation - Alan Agresti and Barbara AgrestiNo Humble Pie: The Origins and Usage of a Statistical Chart - Ian SpenceBah! Bar Charts - Allan ReeseRevising the Pareto Chart - Leland WilkinsonPart Three: The Chi-Square TestKarl Pearson and the Chi-Squared Test - R. PlackettThe Use of Chi-Squared Statistics for Categorical Data Problems - Stephen FienbergSample Size Restraints Commonly Imposed on the Use of the Chi-Square Statistic - John Roscoe and Jackson ByarsWhat Is the Continuity Correction? - Nathan Mantel and Samuel GreenhouseSome Reasons for Not Using the Yates Continuity Correction on 2 ×2 Contingency Tables: Comment and a Suggestion - Nathan MantelPart Four: Exact Inference for Contingency TablesOn the Interpretation of ?2 from Contingency Tables, and the Calculation of P - R. FisherFisher’s Exact Test - Graham UptonA Survey of Exact Inference for Contingency Tables - Alan AgestiPart Five: Measuring the Relationship between Two Ordinal VariablesOn the Association of Attributes in Statistics: With Illustrations from the Material of the Childhood Society, &c - G. Udny YuleA New Measure of Rank Correlation - M. KendallThe Treatment of Ties in Ranking Problems - M. KendallA New Asymmetric Measure of Association for Ordinal Variables - Robert SomersVOLUME TWO: STATISTICAL METHODS FOR ANALYSING ASSOCIATIONSPart One: Simpson’s ParadoxSimpson’s Paradox in Real Life - Clifford WagnerMinority Contributions to the SAT Score Turnaround: An Example of Simpson′s Paradox - Howard WainerConfounding and Collapsibility in Causal Inference - Sander Greenland, James Robins and Judea PearlPart Two: Mobility TablesStatus, Autonomy, and Training in Occupational Mobility - Michael HoutA New Index of Structure for the Analysis of Models for Mobility Tables and Other Cross-Classifications - Clifford Clogg, Tamas Rudas and Liwen XiPart Three: Statistical Tests for High Dimensional TablesPreliminary Graphical Analysis and Quasi-Independence for a Two-Way Contingency Table - Stephen FienbergThe Analysis of Multidimensional Contingency Tables - Stephen FienbergThe Analysis of Incomplete Multi-Way Contingency Tables - Stephen FienbergPartitioning of Chi-Square, Analysis of Marginal Contingency Tables, and Estimation of Expected Frequencies in Multidimensional Contingency Tables - Leo GoodmanPart Four: Association ModelsSimple Models for the Analysis of Association in Cross-Classifications Having Ordered Categories - Leo GoodmanAnalysis of Sets of Two-Way Contingency Tables Using Association Models - Mark Becker and Clifford CloggA Survey of Strategies for Modeling Cross-Classifications Having Ordinal Variables - Alan AgrestiPart Five: Dealing with SparsenessMethods for the Analysis of Contingency Tables with Large and Small Cell Counts - Jenny Baglivo, Donald Oliver and Marcello PaganoGoodness-of-Fit Tests for Loglinear Models in Sparse Contingency Tables - Kenneth KoehlerVOLUME THREE: LOG-LINEAR AND LOGISTIC REGRESSION MODELSPart One: Generalized Linear ModelsGeneralized Linear Models - J. Nelder and R. WedderburnPart Two: Log-Linear ModelsAn Introduction to Categorical Data Analysis - Douglas Sloane and S. Phillip MorganSome Common Problems in Log-Linear Analysis - Clifford Clogg and Scott EliasonPart Three: Logistic Regression ModelsThe Regression Analysis of Binary Sequences - D. CoxA Logistic Model for Paired Comparisons with Ordered Categorical Data - P. McCullaghGraphical Methods for Assessing Logistic Regression Models - James Landwehr, Daryl Pregibon and Anne ShoemakerEvaluating Logistic Models for Large Contingency Tables - Edward Fowlkes, Anne Freeny and James LandwehrA Graphical Method for Assessing the Fit of a Logistic Regression Model - Iain Pardoe and R. Dennis CookPart Four: Multilevel Statistical Models for Categorical Response VariablesThe Intraclass Correlation Coefficient: Distribution-Free Definition and Test - Daniel Commenges and Helene JacqminModeling Clustered Ordered Categorical Data - Alan Agresti and Ranjini NatarajanReligious Attendance in Cross-National Perspective: A Multilevel Analysis of 60 Countries - Stijn Ruiter and Frank van TubergenPart Five: Longitudinal Analysis for Categorical Response VariablesLongitudinal Data Analysis Using Generalized Linear Models - King-Yee Liang and Scott ZegerA Bayesian Hierarchical Model for Categorical Longitudinal Data from a Social Survey of Immigrants - A. Pettitt et al.VOLUME FOUR: ADVANCED AND GRAPHICAL STATISTICAL METHODSPart One: Correspondence AnalysisSimple Correspondence Analysis: A Bibliographic Review - Eric BehSome Useful Extensions of the Usual Correspondence Analysis Approach and the Usual Log-Linear Models Approach in the Analysis of Contingency Tables - Leo GoodmanPart Two: Factor Analysis for Categorical VariablesMultiway Contingency Analysis with a Scaled Response or Factor - Otis Duncan and James McRae, JrFactor Analysis for Categorical Data - D.J. BartholomewPart Three: Latent Class ModelsExploratory Latent Structure Analysis Using Both Identifiable and Unidentifiable Models - Leo GoodmanCategorical Causal Modelling: Latent Class Analysis and Directed Log-Linear Models with Latent Variables - Jacques HagenaarsOn the Assignment of Individuals to Latent Classes - Leo GoodmanPart Four: Missing Values in Categorical DataLoglinear Models with Missing Data: A Latent Class Approach - Christopher Winship and Robert MareMultiple Imputation of Incomplete Categorical Data Using Latent Class Analysis - Jeroen Vermunt et al.Part Five: Graphical MethodsConceptual and Visual Models for Categorical Data - Michael FriendlyMosaic Displays for Multi-Way Contingency Tables - Michael FriendlyExtending Mosaic Displays: Marginal, Conditional, and Partial Views of Categorical Data - Michael FriendlyMultigraph Representations of Hierarchical Loglinear Models - Terry McKee and Harry KhamisLatent Class Factor and Cluster Models, Bi-Plots, and Related Graphical Displays - Jay Magidson and Jeroen Vermunt