Categorical data analysis

• 作者： Agresti, Alan
• 其他題名：
  • Wiley series in probability and statistics
• 出版： Hoboken, NJ : Wiley
• 版本：3rd ed.
• 叢書名： Wiley series in probability and statistics
• 主題： Multivariate analysis
• ISBN： 9780470463635 (hbk.) 、 0470463635 (hbk.)
• 資料類型: 圖書
• 內容註: Includes bibliographical references and index. Introduction: Distributions and inference for categorical data -- Describing contingency tables -- Inference for two-way contingency tables -- Introduction to generalized linear models -- Logistic regression -- Building, checking, and applying logistic regression models -- Alternative modeling of binary response data -- Models for multinomial responses -- Loglinear models for contingency tables -- Building and extending loglinear models -- Models for matched pairs -- Clustered categorical data: marginal and transitional models -- Clustered categorical data: random effects models -- Other mixture models for discrete data -- Non-model-based classification and clustering -- Large- and small-sample theory for multinomial models -- Historical tour of categorical data analysis -- Appendix A: Statistical software for categorical data analysis -- Appendix B: Chi-squared distribution values. Machine generated contents note: Preface 1. Introduction: Distributions and Inference for Categorical Data 1 1.1 Categorical Response Data, 1 1.2 Distributions for Categorical Data 1.3 Statistical Inference for Categorical Data 1.4 Statistical Inference for Binomial Parameters 1.5 Statistical Inference for Multinomial Parameters 1.6 Bayesian Inference for Binomial and Multinomial Parameters Notes Exercises 2. Describing Contingency Tables 2.1 Probability Structure for Contingency Tables 2.2 Comparing Two Proportions 2.3 Conditional Association in Stratified 2x2 Tables 2.4 Measuring Association in I x J Tables Notes Exercises 3. Inference for Two-Way Contingency Tables 3.1 Confidence Intervals for Association Parameters 3.2 Testing Independence in Two-Way Contingency Tables 3.3 Following-Up Chi-Squared Tests 3.4 Two-Way Tables with Ordered Classifications 3.5 Small-Sample Inference for Contingency Tables 3.6 Bayesian Inference for Two-Way Contingency Tables 3.7 Extensions for Multiway Tables and Nontabulated Responses Notes Exercises 4. Introduction to Generalized Linear Models 4.1 The Generalized Linear Model 4.2 Generalized Linear Models for Binary Data 4.3 Generalized Linear Models for Counts and Rates 4.4 Moments and Likelihood for Generalized Linear Models 4.5 Inference and Model Checking for Generalized Linear Models 4.6 Fitting Generalized Linear Models 4.7 Quasi-Likelihood and Generalized Linear Models Notes Exercises 5. Logistic Regression 5.1 Interpreting Parameters in Logistic Regression 5.2 Inference for Logistic Regression 5.3 Logistic Models with Categorical Predictors 5.4 Multiple Logistic Regression 5.5 Fitting Logistic Regression Models Notes Exercises 6. Building, Checking, and Applying Logistic Regression Models 6.1 Strategies in Model Selection 6.2 Logistic Regression Diagnostics 6.3 Summarizing the Predictive Power of a Model 6.3 Mantel-Haenszel and Related Methods for Multiple 2x2 Tables 6.4 Detecting and Dealing with Infinite Estimates 6.5 S
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• 摘要註: "A classic in its own right, this book continues to provide an introduction to modern generalized linear models for categorical variables. The text emphasizes methods that are most commonly used in practical application, such as classical inferences for two- and three-way contingency tables, logistic regression, loglinear models, models for multinomial (nominal and ordinal) responses, and methods for repeated measurement and other forms of clustered, correlated response data. Chapter headings remain essentially with the exception of a new one on Bayesian inference for parametric models. Other major changes include an expansion of clustered data, new research on analysis of data sets with robust variables, extensive discussions of ordinal data, more on interpretation, and additional exercises throughout the book. R and SAS are now showcased as the software of choice. An author web site with solutions, commentaries, software programs, and data sets is available"--
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