Rent 9780470082898 | Analysis of Ordinal Categorical Data

Summary Table of Contents Author Biography

Praise for the First Edition:"The author has a fluent, easy-to-read style, and well-chosen interesting material to present and illustrate the ideas to the newcomer and the old hand alike."-Journal of the Royal Statistical SocietyCategorical data having ordered categories are common in practice, especially in applications throughout the biomedical and social sciences. Thoroughly updated to reflect developments since the publication of its predecessor, Analysis of Ordinal Categorical Data, Second Edition presents a comprehensive survey of methods... MORE for analyzing ordinal categorical data, complete with coverage of the most recent research.The author highlights various modeling techniques, including cumulative logit models with and without proportional odds structure, adjacent-categories logit and continuation-ratio logit models, stereotype models, association models for ordinal odds ratios, and models for clustered ordinal data. Additional features of this Second Edition include:A new chapter on marginal models for multivariate ordinal responses, using maximum likelihood and generalized estimating equations for model fittingA new chapter on random effects models for clustered ordinal dataA new chapter on Bayesian approaches for analyzing ordinal dataModels and order-restricted inference methods for various types of ordinal odds ratios, including local odds ratios, cumulative odds ratios, and global odds ratiosPresentation of non-model-based methods, such as nonparametric rank methods that also apply to ordered categorical dataEach chapter concludes with notes on relevant research literature as well as exercises that allow readers to test their comprehension of the presented concepts. A detailed appendix discusses the use of the latest software such as SASr, R, SPSSr, and Statar, and the book's related Web site provides further instructions for the use of these software packages along with complete data sets.Analysis of Ordinal Categorical Data, Second Edition is an excellent book for courses on categorical data analysis at the upper-undergraduate and graduate levels. It is also an invaluable resource for researchers and practitioners who conduct data analysis in the areas of public health, business, medicine, and the social and behavioral sciences.

Statistical science s first coordinated manual of methods for analyzing ordered categorical data presents applications and case studies in fields as diverse as sociology, public health, ecology, marketing, and pharmacy. Analysis of Ordinal Categorical Data provides an introduction to basic descriptive and inferential methods for categorical data and gives thorough coverage of late developments. Special emphasis is placed on interpretation and application of methods including an integrated comparison of the available strategies for analyzing ordinal data. The book also discusses implementation of methods using computer packages such as SAS, SPSSx, and GLIM.

Statistical sciencers"s first coordinated manual of methods for analyzing ordered categorical data, now fully revised and updated, continues to present applications and case studies in fields as diverse as sociology, public health, ecology, marketing, and pharmacy.

Preface	p. ix
Introduction	p. 1
Ordinal Categorical Scales	p. 1
Advantages of Using Ordinal Methods	p. 2
Ordinal Modeling Versus Ordinary Regession Analysis	p. 4
Organization of This Book	p. 8
Ordinal Probabilities, Scores, and Odds Ratios	p. 9
Probabilities and Scores for an Ordered Categorical Scale	p. 9
Ordinal Odds Ratios for Con... MOREtingency Tables	p. 18
Confidence Intervals for Ordinal Association Measures	p. 26
Conditional Association in Three-Way Tables	p. 35
Category Choice for Ordinal Variables	p. 37
Chapter Notes	p. 41
Exercises	p. 42
Logistic Regression Models Using Cumulative Logits	p. 44
Types of Logits for An Ordinal Response	p. 44
Cumulative Logit Models	p. 46
Proportional Odds Models: Properties and Interpretations	p. 53
Fitting and Inference for Cumulative Logit Models	p. 58
Checking Cumulative Logit Models	p. 67
Cumulative Logit Models Without Proportional Odds	p. 75
Connections with Nonparametric Rank Methods	p. 80
Chapter Notes	p. 84
Exercises	p. 87
Other Ordinal Logistic Regression Models	p. 88
Adjacent-Categories Logit Models	p. 88
Continuation-Ratio Logit Models	p. 96
Stereotype Model: Multiplicative Paired-Category Logits	p. 103
Chapter Notes	p. 115
Exercises	p. 117
Other Ordinal Multinomial Response Models	p. 118
Cumulative Link Models	p. 118
Cumulative Probit Models	p. 122
Cumulative Log-Log Links: Proportional Hazards Modeling	p. 125
Modeling Location and Dispersion Effects	p. 130
Ordinal ROC Curve Estimation	p. 132
Mean Response Models	p. 137
Chapter Notes	p. 140
Exercises	p. 142
Modeling Ordinal Association Structure	p. 145
Ordinary Loglinear Modeling	p. 145
Loglinear Model of Linear-by-Linear Association	p. 147
Row or Column Effects Association Models	p. 154
Association Models for Multiway Tables	p. 160
Multiplicative Association and Correlation Models	p. 167
Modeling Global Odds Ratios and Other Associations	p. 176
Chapter Notes	p. 180
Exercises	p. 182
Non-Model-Based Analysis of Ordinal Association	p. 184
Concordance and Discordance Measures of Association	p. 184
Correlation Measures for Contingency Tables	p. 192
Non-Model-Based Inference for Ordinal Association Measures	p. 194
Comparing Singly Ordered Multinomials	p. 199
Order-Restricted Inference with Inequality Constraints	p. 206
Small-Sample Ordinal Tests of Independence	p. 211
Other Rank-Based Statistical Methods for Ordered Categories	p. 214
Appendix: Standard Errors for Ordinal Measures	p. 216
Chapter Notes	p. 219
Exercises	p. 222
Matched-Pairs Data with Ordered Categories	p. 225
Comparing Marginal Distributions for Matched Pairs	p. 226
Models Comparing Matched Marginal Distributions	p. 231
Models for The Joint Distribution in A Square Table	p. 235
Comparing Marginal Distributions for Matched Sets	p. 240
Analyzing Rater Agreement on an Ordinal Scale	p. 247
Modeling Ordinal Paired Preferences	p. 252
Chapter Notes	p. 258
Exercises	p. 260
Clustered Ordinal Responses: Marginal Models	p. 262
Marginal Ordinal Modeling with Explanatory Variables	p. 263
Marginal Ordinal Modeling: GEE Methods	p. 268
Transitional Ordinal Modeling, Given the Past	p. 274
Chapter Notes	p. 277
Exercises	p. 279
Clustered Ordinal Responses: Random Effects Models	p. 281
Ordinal Generalized Linear Mixed Models	p. 282
Examples of Ordinal Random Intercept Models	p. 288
Models with Multiple Random Effects	p. 294
Multilevel (Hierarchical) Ordinal Models	p. 303
Comparing Random Effects Models and Marginal Models	p. 306
Chapter Notes	p. 312
Exercises	p. 314
Bayesian Inference for Ordinal Response Data	p. 315
Bayesian Approach to Statistical Inference	p. 316
Estimating Multinomial Parameters	p. 319
Bayesian Ordinal Regression Modeling	p. 327
Bayesian Ordinal Association Modeling	p. 335
Bayesian Ordinal Multivariate Regression Modeling	p. 339
Bayesian Versus Frequentist Approaches to Analyzing Ordinal Data	p. 341
Chapter Notes	p. 342
Exercises	p. 344
Appendix: Software for Analyzing Ordinal Categorical Data	p. 345
Bibliography	p. 359
Example Index	p. 389
Subject Index	p. 391
Table of Contents provided by Ingram. All Rights Reserved.

ALAN AGRESTI, PhD, is Distinguished Professor Emeritus in the Department of Statistics at the University of Florida and Visiting Professor in the Department of Statistics at Harvard University. A Fellow of the American Statistical Association and the Institute of Mathematical Statistics, Dr. Agresti has published extensively on the topic of categorical data analysis and has presented lectures and short courses on the subject in more than thirty countries. He is the author of Categorical Data Analysis, Second Edition and An Introduction to Categorical Data Analysis, Second Edition, both published by Wiley.

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