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• catalog abstract "This book examines statistical models for frequency data. The primary focus is on log-linear models for contingency tables,but in this second edition,greater emphasis has been placed on logistic regression. Topics such as logistic discrimination and generalized linear models are also explored. The treatment is designed for students with prior knowledge of analysis of variance and regression. It builds upon the relationships between these basic models for continuous data and the analogous log- linear and logistic regression models for discrete data. While emphasizing similarities between methods for discrete and continuous data,this book also carefully examines the differences in model interpretations and evaluation that occur due to the discrete nature of the data. Sample commands are given for analyses in SAS,BMFP,and GLIM. Numerous data sets from fields as diverse as engineering, education,sociology,and medicine are used to illustrate procedures and provide exercises. This book incorporates a number of innovative features. It begins with an extensive discussion of odds and odds ratios as well as concrete illustrations of the basic independence models for contingency tables. After developing a sound applied and theoretical basis for the models considered,the book presents detailed discussions of the use of graphical models and of models selection procedures. It then explores models with quantitative factors and generalized linear models,after which the fundamental results are reexamined using powerful matrix methods. Finally, the book gives an extensive treatment of Bayesian procedures for analyzing logistic regression and other regression models for binomial data. Bayesian methods are simple and,unlike".
• catalog contributor b10514241.
• catalog contributor b10514242.
• catalog created "1997.".
• catalog date "1997".
• catalog date "1997.".
• catalog dateCopyrighted "1997.".
• catalog description "Includes bibliographical references and index.".
• catalog description "Preface to the Second Edition -- Preface to the First Edition -- Introduction -- Two-Dimensional Tables and Simple Logistic Regression -- Three-Dimensional Tables -- Logistic Regression, Logit Models, and Logistic Discrimination -- Independence Relationships and Graphics Models -- Model Selection Methods and Model Evaluation -- Models for Factors with Quantitative Levels -- Fixed and Random Zeros -- Generalized Linear Models -- The Matrix Approach to Log- Linear Models -- The Matrix Approach to Logit Models -- Maximum Likelihood Theory for Log-Linear Models -- Baeyesian Binomial Regression. Appendix A: Tables.".
• catalog description "This book examines statistical models for frequency data. The primary focus is on log-linear models for contingency tables,but in this second edition,greater emphasis has been placed on logistic regression. Topics such as logistic discrimination and generalized linear models are also explored. The treatment is designed for students with prior knowledge of analysis of variance and regression. It builds upon the relationships between these basic models for continuous data and the analogous log- linear and logistic regression models for discrete data. While emphasizing similarities between methods for discrete and continuous data,this book also carefully examines the differences in model interpretations and evaluation that occur due to the discrete nature of the data. Sample commands are given for analyses in SAS,BMFP,and GLIM. Numerous data sets from fields as diverse as engineering, education,sociology,and medicine are used to illustrate procedures and provide exercises. This book incorporates a number of innovative features. It begins with an extensive discussion of odds and odds ratios as well as concrete illustrations of the basic independence models for contingency tables. After developing a sound applied and theoretical basis for the models considered,the book presents detailed discussions of the use of graphical models and of models selection procedures. It then explores models with quantitative factors and generalized linear models,after which the fundamental results are reexamined using powerful matrix methods. Finally, the book gives an extensive treatment of Bayesian procedures for analyzing logistic regression and other regression models for binomial data. Bayesian methods are simple and,unlike".
• catalog extent "xv, 483 p. ;".
• catalog identifier "0387982477".
• catalog isPartOf "Springer texts in statistics".
• catalog issued "1997".
• catalog issued "1997.".
• catalog language "eng".
• catalog publisher "New York : Springer,".
• catalog subject "519.5/35 21".
• catalog subject "Log-linear models.".
• catalog subject "QA278 .C49 1997".
• catalog subject "Statistics.".
• catalog tableOfContents "Preface to the Second Edition -- Preface to the First Edition -- Introduction -- Two-Dimensional Tables and Simple Logistic Regression -- Three-Dimensional Tables -- Logistic Regression, Logit Models, and Logistic Discrimination -- Independence Relationships and Graphics Models -- Model Selection Methods and Model Evaluation -- Models for Factors with Quantitative Levels -- Fixed and Random Zeros -- Generalized Linear Models -- The Matrix Approach to Log- Linear Models -- The Matrix Approach to Logit Models -- Maximum Likelihood Theory for Log-Linear Models -- Baeyesian Binomial Regression. Appendix A: Tables.".
• catalog title "Log-linear models and logistic regression / Ronald Christensen.".
• catalog type "text".