Applied Categorical Data Analysis and

This new edition continues to provide basic, comprehensive coverage of key methods in categorical data analysis with multiple variables. Maintaining the same nontechnical, user-friendly approach, coverage has been added to the Second Edition to take the topic of categorical data analysis into a more applied direction. Coverage begins with an introduction to the basic methods and applications of contingency tables and loglinear models. Subsequent chapters examine analytical methods for matched data and count data, the Mantel-Haenszel method, Kappa statistics, ordinal risks, odds ratio estimates, goodness-of-fit, and various regression models for categorical data. The chapter on logistic regression models has been completely revised, with a new section on quantal bioassays and updated coverage of modeling probabilities, now incorporating new models such as PROBIT. A new chapter on diagnostic medicine incorporates the previous edition's discussion of screening tests and ROC curves and another added chapter introduces early-phase clinical trials, including detailed coverage of design for Phase I and Phase II clinical trials. Exercises and examples have been updated and added throughout, and the inclusion of SAS codes has been maintained to assist readers with the analysis and interpretation of the presented data.

Chap T. Le, PhD, is Distinguished Professor and Director of Biostatistics at the University of Minnesota Cancer Center. In addition to providing statistical consulting for a variety of biomedical research projects, he has worked on collaborations that have focused on the analyses of survival and categorical data and, currently, in the areas of cancer and tobacco research. Dr. Le is the author of Health and Numbers: A Problems Based Introduction to Biostatistics, Third Edition; Introductory Biostatistics; and Applied Survival Analysis, all published by Wiley.

Preface	p. xiii
Preface to First Edition	p. xv
Introduction	p. 1
A Prototype Example	p. 2
A Review of Likelihood-Based Methods	p. 5
Interval Estimation for a Proportion	p. 11
About This Book	p. 13
Contingency Tables	p. 15
Some Sampling Models for Categorical Data	p. 16
The Binomial and Multinomial Distributions	p. 16
The Hypergeometric Distributions	p. 19
Inferences for 2-by-2 Contingency Tables	p. 22
Comparison of Two Proportions	p. 22
Tests for Independence	p. 28
Fisher's Exact Test	p. 30
Relative Risk and Odds Ratio	p. 32
Etiologic Fraction	p. 41
Crossover Designs	p. 43
The Mantel-Haenszel Method	p. 45
Inferences for General Two-Way Tables	p. 51
Comparison of Several Proportions	p. 52
Testing for Independence in Two-Way Tables	p. 53
Ordered 2-by-k Contingency Tables	p. 55
Sample Size Determination	p. 60
Exercises	p. 62
Loglinear Models	p. 72
Loglinear Models for Two-Way Tables	p. 74
Loglinear Models for Three-Way Tables	p. 76
The Models of Independence	p. 78
Relationships Between Terms and Hierarchy of Models	p. 79
Testing a Specific Model	p. 80
Searching for the Best Model	p. 88
Collapsing Tables	p. 92
Loglinear Models for Higher-Dimensional Tables	p. 92
Testing a Specific Model	p. 93
Searching for the Best Model	p. 95
Measures of Association with an Effect Modification	p. 99
Searching for a Model with a Dependent Variable	p. 104
Exercises	p. 105
Logistic Regression Models	p. 113
Modeling a Probability	p. 116
The Logarithmic Transformation	p. 118
The Probit Transformation	p. 118
The Logistic Transformation	p. 119
Simple Regression Analysis	p. 119
The Logistic Regression Model	p. 120
Measure of Association	p. 121
Tests of Association	p. 124
Use of the Logistic Model for Different Designs	p. 124
Overdispersion	p. 125
Multiple Regression Analysis	p. 128
Logistic Regression Model with Several Covariates	p. 128
Effect Modifications	p. 130
Polynomial Regression	p. 131
Testing Hypotheses in Multiple Logistic Regression	p. 132
Measures of Goodness-of-Fit	p. 140
Ordinal Logistic Model	p. 142
Quantal Bioassays	p. 145
Types of Bioassays	p. 146
Quantal Response Bioassays	p. 147
Exercises	p. 150
Methods for Matched Data	p. 158
Measuring Agreement	p. 159
Pair-Matched Case-Control Studies	p. 162
The Model	p. 162
The Analysis	p. 164
The Case of Small Samples	p. 167
Risk Factors with Multiple Categories and Ordinal Risks	p. 169
Multiple Matching	p. 171
The Conditional Approach	p. 171
Estimation of the Odds Ratio	p. 172
Testing for Exposure Effect	p. 173
Testing for Homogeneity	p. 175
Conditional Logistic Regression	p. 176
Simple Regression Analysis	p. 177
Multiple Regression Analysis	p. 182
Exercises	p. 189
Methods for Count Data	p. 198
The Poisson Distribution	p. 198
Testing Goodness-of-Fit	p. 202
The Poisson Regression Model	p. 204
Simple Regression Analysis	p. 206
Multiple Regression Analysis	p. 208
Overdispersion	p. 215
Stepwise Regression	p. 217
Exercise	p. 219
Categorical Data and Translational Research	p. 227
Types of Clinical Studies	p. 228
From Bioassays to Translational Research	p. 230
Analysis of In Vitro Experiments	p. 231
Design and Analysis of Experiments for Combination Therapy	p. 234
Phase I Clinical Trials	p. 238
Standard Design	p. 238
Fast Tracts Design	p. 243
Continual Reassessment Method	p. 247
Phase II Clinical Trials	p. 253
Sample Size Determination for Phase II Clinical Trials	p. 255
Phase II Clinical Trial Designs for Selection	p. 259
Two-Stage Phase II Design	p. 264
Toxicity Monitoring in Phase II Trials	p. 271
Multiple Decisions	p. 279
Exercises	p. 285
Categorical Data and Diagnostic Medicine	p. 289
Some Examples	p. 290
The Diagnosis Process	p. 294
The Developmental Stage	p. 294
The Applicational Stage	p. 298
Some Statistical Issues	p. 302
The Response Rate	p. 302
The Issue of Population Random Testing	p. 303
Screenable Disease Prevalence	p. 304
An Index for Diagnostic Competence	p. 306
Prevalence Surveys	p. 308
Known Sensitivity and Specificity	p. 309
Unknown Sensitivity and Specificity	p. 312
Prevalence Survey with a New Test	p. 315
The Receiver Operating Characteristic Curve	p. 317
The ROC Function and ROC Curve	p. 317
Some Parametric ROC Models	p. 319
Estimation of the ROC Curve	p. 320
Index for Diagnostic Accuracy	p. 322
Estimation of Area Under ROC Curve	p. 323
The Optimization Problem	p. 325
Basic Criterion: Youden's Index	p. 326
Possible Solutions	p. 327
Statistical Considerations	p. 331
Evaluation of Screening Tests	p. 332
Comparison of Screening Tests	p. 333
Consideration of Subjects' Characteristics	p. 338
Exercises	p. 340
Transition from Categorical to Survival Data	p. 342
Survival Data	p. 343
Introductory Survival Analysis	p. 346
Kaplan-Meier Curve	p. 346
Comparison of Survival Distributions	p. 349
Simple Regression and Correlation	p. 353
Model and Approach	p. 354
Measures of Association	p. 355
Tests of Association	p. 357
Multiple Regression and Correlation	p. 358
Proportional Hazards Models with Several Covariates	p. 358
Testing Hypotheses in Multiple Regression	p. 359
Time-Dependent Covariates and Applications	p. 364
Competing Risks	p. 367
Redistribution to the Right Method	p. 368
Estimation of the Cumulative Incidence	p. 370
Brief Discussion of Proportional Hazards Regression	p. 374
Exercise	p. 376
Bibliography	p. 383
Index	p. 393
Table of Contents provided by Ingram. All Rights Reserved.

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Applied Categorical Data Analysis and Translational Research

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