Erling B. Andersen

Introduction to the Statistical Analysis of Categorical Data

• Broschiertes Buch

Produktbeschreibung

This book deals with the analysis of categorical data. Statistical models, especially log-linear models for contingency tables and logistic regression, are described and applied to real life data. Special emphasis is given to the use of graphical methods. The book is intended as a text for both undergraduate and graduate courses for statisticians, applied statisticians, social scientists, economists and epidemiologists. Many examples and exercises with solutions should help the reader to understand the material.

---

to the Statistical Analysis of Categorical Data With 16 Figures and 121 Tables , Springer Prof. Erling B. Andersen University of Copenhagen Department of Statistics 6 Studiestrrede DK-14SS Copenhagen Denmark ISBN 978-3-540-62399-1 CataJoging-in-Publication Data applied ror Oie Oeutsche Bibliothek - CIP-Einheitsaufnahme Andersen, Erling B. : Introduction to the statistical analysis of categorical data analysis: with 121 tables I Erling B. Andersen. -Berlin; Heidelberg; New York; Bucelona; Buda pest; Hong Kong; London; Milan; Paris; Santa Clara; Singapore; Tokyo: Springer, 1997 ISBN 978-3-540~2399-1 ISBN 978-3~2-59123-5 (eBook) DOI10. 1007/978-3~2-59123-5 This work is subject to copyright. AII rights are reserved, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilm or in any o!her way, and storage in data banks. Ouplication of this publication or partsthereof IS permitted only under the provisions of !he German Copyright Law of September 9, 1965, in its current version, and permission for use must always be obtained from Springer-Verlag. Violations are liable for prosecution under !he German Copyright Law. O Springer-Verlag Berlin Heidelberg 1997 Originally published by Springer-Verlag Berlin Heidelberg New York in 1997 The use of general descriptive names, registered names, trademarks, etc. in this publi cation does not imply, even in !he absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and !herefore free for general use.

Produktdetails

• Verlag: Springer / Springer Berlin Heidelberg / Springer, Berlin
• Artikelnr. des Verlages: 978-3-540-62399-1
• 1997.
• Seitenzahl: 276
• Erscheinungstermin: 20. März 1997
• Englisch
• Abmessung: 235mm x 155mm x 16mm
• Gewicht: 418g
• ISBN-13: 9783540623991
• ISBN-10: 354062399X
• Artikelnr.: 06917890

Inhaltsangabe

1 Introduction.- 1.1 The two-way table.- 2 Basic Theory.- 2.1 Introduction.- 2.2 Exponential families.- 2.3 Statistical inference in an exponential family.- 2.4 The binomial distribution.- 2.5 The multinomial distribution.- 2.6 The Poisson distribution.- 2.7 Composite hypotheses.- 2.8 Applications to the multinomial distribution.- 2.9 Log-linear models.- 2.10 The two-way contingency table.- 2.11 The numerical solution of the likelihood equations for the log-linear model.- 2.12 Bibliographical notes.- 2.13 Exercises.- 3 Three-way contingency tables.- 3.1 Log-linear models.- 3.2 Log-linear hypotheses.- 3.3 Estimation.- 3.4 Testing hypotheses.- 3.5 Interpretation of the log-linear parameters.- 3.6 Choice of model.- 3.7 Detection of model deviations.- 3.8 Bibliographical notes.- 3.9 Exercises.- 4 Multi-dimensional contingency tables.- 4.1 The log-linear model.- 4.2 Classification and interpretation of log-linear models.- 4.3 Choice of model.- 4.4 Diagnostics.- 4.5 Model search strategies.- 4.6 Bibliographical notes.- 4.7 Exercises.- 5 Incomplete Tables.- 5.1 Random and structural zeros.- 5.2 Counting the number of degrees of freedom.- 5.3 Validity of the X2-approximation.- 5.4 Exercises.- 6 The Logit Model.- 6.1 The logit model.- 6.2 Hypothesis testing in the logit model.- 6.3 Logit models with higher order interactions.- 6.4 The logit model as a regression model.- 6.5 Bibliographical notes.- 6.6 Exercises.- 7 Logistic Regression Analysis.- 7.1 The logistic regression model.- 7.2 Estimation in the logistic regression model.- 7.3 Numerical solution of the likelihood equations.- 7.4 Checking the fit of the model.- 7.5 Hypothesis testing.- 7.6 Diagnostics.- 7.7 Predictions.- 7.8 Dummy variables.- 7.9 Polytomous response variables.- 7.10 Bibliographical notes.- 7.11 Exercises.-8 Association Models.- 8.1 Introduction.- 8.2 Symmetry models.- 8.3 Marginal homogeneity.- 8.4 RC-association models.- 8.5 Correspondence analysis.- 8.6 Bibliographical notes.- 8.5 Exercises.- Appendix Solutions and output to selected exercises.- References.