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This book will serve as a reference and a graduate textbook in the area of categorical data analysis. It includes data sets from engineering, education, sociology, and medicine. Professor Christensen is the successful author of four graduate-level texts.
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The primary focus here is on log-linear models for contingency tables, but in this second edition, greater emphasis has been placed on logistic regression. The book explores topics such as logistic discrimination and generalised linear models, and builds upon the relationships between these basic models for continuous data and the analogous log-linear and logistic regression models for discrete data. It also carefully examines the differences in model interpretations and evaluations that occur due to the discrete nature of the data. Sample commands are given for analyses in SAS, BMFP, and GLIM, while numerous data sets from fields as diverse as engineering, education, sociology, and medicine are used to illustrate procedures and provide exercises. Throughoutthe book, the treatment is designed for students with prior knowledge of analysis of variance and regression.
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Log-Linear Models and Logistic Regression (Springer Texts in Statistics) Second Edition
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Log-Linear Models and Logistic Regression
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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. The primary focus here is on log-linear models for contingency tables, but in this second edition, greater emphasis has been placed on logistic regression. The book explores topics such as logistic discrimination and generalised linear models, and builds up. Bestandsnummer des Verkäufers 4207699
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Log-Linear Models and Logistic Regression
Verlag:
Springer New York, Springer New York Mär 2013, 2013
ISBN 10: 1475771134
ISBN 13: 9781475771138
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Taschenbuch. Zustand: Neu. Neuware -As the new title indicates, this second edition of Log-Linear Models has been modi ed to place greater emphasis on logistic regression. In addition to new material, the book has been radically rearranged. The fundamental material is contained in Chapters 1-4. Intermediate topics are presented in Chapters 5 through 8. Generalized linear models are presented in Ch- ter 9. The matrix approach to log-linear models and logistic regression is presented in Chapters 10-12, with Chapters 10 and 11 at the applied Ph.D. level and Chapter 12 doing theory at the Ph.D. level. The largest single addition to the book is Chapter 13 on Bayesian bi- mial regression. This chapter includes not only logistic regression but also probit and complementary log-log regression. With the simplicity of the Bayesian approach and the ability to do (almost) exact small sample s- tistical inference, I personally nd it hard to justify doing traditional large sample inferences. (Another possibility is to do exact conditional inference, but that is another story.) Naturally,Ihavecleaneduptheminor awsinthetextthatIhavefound. All examples, theorems, proofs, lemmas, etc. are numbered consecutively within each section with no distinctions between them, thus Example 2.3.1 willcomebeforeProposition2.3.2.Exercisesthatdonotappearinase ction at the end have a separate numbering scheme. Within the section in which it appears, an equation is numbered with a single value, e.g., equation (1).Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 504 pp. Englisch. Bestandsnummer des Verkäufers 9781475771138
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Log-Linear Models and Logistic Regression
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The primary focus here is on log-linear models for contingency tables, but in this second edition, greater emphasis has been placed on logistic regression. The book explores topics such as logistic discrimination and generalised linear models, and builds upon the relationships between these basic models for continuous data and the analogous log-linear and logistic regression models for discrete data. It also carefully examines the differences in model interpretations and evaluations that occur due to the discrete nature of the data. Sample commands are given for analyses in SAS, BMFP, and GLIM, while numerous data sets from fields as diverse as engineering, education, sociology, and medicine are used to illustrate procedures and provide exercises. Throughoutthe book, the treatment is designed for students with prior knowledge of analysis of variance and regression. 504 pp. Englisch. Bestandsnummer des Verkäufers 9781475771138
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Log-Linear Models and Logistic Regression
Verlag:
Springer New York, Springer New York, 2013
ISBN 10: 1475771134
ISBN 13: 9781475771138
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Taschenbuch
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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - As the new title indicates, this second edition of Log-Linear Models has been modi ed to place greater emphasis on logistic regression. In addition to new material, the book has been radically rearranged. The fundamental material is contained in Chapters 1-4. Intermediate topics are presented in Chapters 5 through 8. Generalized linear models are presented in Ch- ter 9. The matrix approach to log-linear models and logistic regression is presented in Chapters 10-12, with Chapters 10 and 11 at the applied Ph.D. level and Chapter 12 doing theory at the Ph.D. level. The largest single addition to the book is Chapter 13 on Bayesian bi- mial regression. This chapter includes not only logistic regression but also probit and complementary log-log regression. With the simplicity of the Bayesian approach and the ability to do (almost) exact small sample s- tistical inference, I personally nd it hard to justify doing traditional large sample inferences. (Another possibility is to do exact conditional inference, but that is another story.) Naturally,Ihavecleaneduptheminor awsinthetextthatIhavefound. All examples, theorems, proofs, lemmas, etc. are numbered consecutively within each section with no distinctions between them, thus Example 2.3.1 willcomebeforeProposition2.3.2.Exercisesthatdonotappearinasection at the end have a separate numbering scheme. Within the section in which it appears, an equation is numbered with a single value, e.g., equation (1). Bestandsnummer des Verkäufers 9781475771138
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Log-Linear Models and Logistic Regression (Springer Texts in Statistics)
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Log-Linear Models and Logistic Regression (Springer Texts in Statistics)
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Log-Linear Models and Logistic Regression
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Log-Linear Models and Logistic Regression
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