The Analysis Of Cross-classified Categorical Data

Paperback | July 30, 2007

byStephen E. Fienberg

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A variety of biological and social science data come in the form of cross-classified tables of counts, commonly referred to as contingency tables. Until recent years the statistical and computational techniques available for the analysis of cross-classified data were quite limited. This book presents some of the recent work on the statistical analysis of cross-classified data using longlinear models, especially in the multidimensional situation.

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A variety of biological and social science data come in the form of cross-classified tables of counts, commonly referred to as contingency tables. Until recent years the statistical and computational techniques available for the analysis of cross-classified data were quite limited. This book presents some of the recent work on the stat...

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Format:PaperbackDimensions:212 pages, 8.27 × 5.83 × 0.27 inPublished:July 30, 2007Publisher:Springer New YorkLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:0387728244

ISBN - 13:9780387728247

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Table of Contents

Introduction.- Two-dimensional tables.- Three-dimensional tables.- Selection of a model.- Four- and higher-dimensional contingency tables.- Fixed margins and logit models.- Causal analysis involving logit and loglinear models.- Fixed and random zeroes.

Editorial Reviews

From the reviews of the second edition:"This is a great book on the analysis of cross-classified categorical data, particularly for non-statistical readers. The need for analyzing cross-classified categorical data has been growing rapidly . . The loglinear models and maximum-likelihood estimates discussed in this book are very helpful for practitioners to get hands on categorical data and perform sound analyses. This book is comprised of 8 chapters. . is a useful book and I recommend it to data analysts in practical and academic fields." (Zhen Mei, Zentralblatt MATH, Vol. 1134 (12), 2008)"This Springer edition is a reprint of the first edition published by MIT Press in 1977. . this a useful resource book for applied statisticians with good theoretical background." (Technometrics, Vol. 50 (4), November, 2008)