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The Analysis of Contingency Tables

Autor Brian S. Everitt
en Limba Engleză Paperback – 2 dec 2019
Much of the data collected in medicine and the social sciences is categorical, for example, sex, marital status, blood group, whether a smoker or not and so on, rather than interval-scaled. Frequently the researcher collecting such data is interested in the relationships or associations between pairs, or between a set of such categorical variables; often the data is displayed in the form of a contingency table for example, smoker versus non-smoker against death from lung cancer or death from some other cause. This text gives a comprehensive account of the analysis of such tables, written at a level suitable for the applied researcher. The first edition of "The Analysis of Contingency Tables" arose from Professor A.E. Maxwell's earlier text, "Analysing Qualitative Data". In this new edition, more material is included that those methods which have developed over the last decade or so, for example, logistic regression models for tables with ordered categories and for response variables with more than two categories. A brief account is given of the increasingly important technique, correspondence analysis. The methods of analysis described in this book should be relevant to research workers and graduate students dealing with data from surveys, particularly in the area of psychiatry, social sciences and psychology.
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Specificații

ISBN-13: 9780367450410
ISBN-10: 0367450410
Pagini: 168
Dimensiuni: 152 x 229 x 10 mm
Greutate: 0.45 kg
Ediția:2nd edition
Editura: CRC Press
Colecția Chapman and Hall/CRC

Public țintă

Professional Practice & Development

Cuprins

1. Contingency tables and the chi-square test 2. 2x 2 contingency tables 3. r x c contingency tables 4. Multidimensional tables 5. Log-linear models for contingency tables 6. Linear-logistic models 7. Contingency tables with ordered categories 8. Some special types of contingency table

Descriere

This book is primarily concerned with methods of analysis for frequency data occurring in the form of cross-classifications or contingency tables. It explains logistic regression models for tables with ordered categories and for response variables with more than two categories.