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Publicado por Springer, New York, 1997
ISBN 10: 0387982477 ISBN 13: 9780387982472
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Añadir al carritoHardcover. Condición: Near fine. Second Edition. Springer Texts in Statistics. xv, 483 p. 24 cm. Numerous figures. Hardcover. Small dent in bottom of front board. Topics: two-dimensional tables and simple logistic regression; three-dimensional tables; logistic regression, logit models; independence relationships and graphical models; models for factors with quantitative levels; fixed and random zeros; generalized linear models; the matrix approach to log-linear models; matrix approach to logit models; Bayesian binomial regression; etc. Index.
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Añadir al carritoTaschenbuch. Condición: Neu. Log-Linear Models and Logistic Regression | Ronald Christensen | Taschenbuch | xvi | Englisch | 2013 | Springer New York | EAN 9781475771138 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Publicado por Springer New York, Springer New York Mär 2013, 2013
ISBN 10: 1475771134 ISBN 13: 9781475771138
Idioma: Inglés
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Añadir al carritoTaschenbuch. Condición: 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.
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Publicado por Springer New York, Springer New York, 2013
ISBN 10: 1475771134 ISBN 13: 9781475771138
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Añadir al carritoTaschenbuch. Condición: 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).
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Publicado por Springer Nature Switzerland, Springer International Publishing, 2025
ISBN 10: 3031690370 ISBN 13: 9783031690372
Idioma: Inglés
Librería: AHA-BUCH GmbH, Einbeck, Alemania
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Añadir al carritoBuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book examines statistical models for frequency data. The primary focus is on log-linear models for contingency tables but also includes extensive discussion of logistic regression. Topics such as logistic discrimination, generalized linear models, and correspondence analysis are also explored.The treatment is designed for readers 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. Numerous data sets from fields as diverse as engineering, education, sociology, and medicine are used to illustrate procedures and provide exercises. A major addition to the third edition is the availability of a companion online manual providing R code for the procedures illustrated in the book.The book begins with an extensive discussion of odds and odds ratios as well as concrete illustrations of basic independence models for contingency tables. After developing a sound applied and theoretical basis for frequency models analogous to ANOVA and regression, the book presents, for contingency tables, detailed discussions of the use of graphical models, of model selection procedures, and of models with quantitative factors. It then explores generalized linear models, after which all the fundamental results are reexamined using powerful matrix methods. The book then gives an extensive treatment of Bayesian procedures for analyzing logistic regression and other regression models for binomial data. Bayesian methods are conceptually simple and unlike traditional methods allow accurate conclusions to be drawn without requiring large sample sizes. The book concludes with two new chapters: one on exact conditional tests for small sample sizes and another on the graphical procedure known as correspondence analysis.
EUR 225,03
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Añadir al carritoHardcover. Condición: Brand New. 3rd edition. 566 pages. 9.25x6.10x9.21 inches. In Stock.
Publicado por Springer, University of New Mexico, 1997
Librería: Montreal Books, Westmount, QC, Canada
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Añadir al carritoHardcover. Condición: Fine. Book.
Publicado por Springer, University of New Mexico, 1997
Librería: RPBooks, Champlain, NY, Estados Unidos de America
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Añadir al carritoHardcover. Condición: Fine. Book.
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Añadir al carritoHardcover. Condición: Sehr gut. 2. Auflage. GERINGE LAGERSPUREN, SONST SEHR GUT, nur A-814.