Stephen E. Fienberg

The Analysis of Cross-Classified Categorical Data (eBook, PDF)

• Format: PDF

Produktbeschreibung

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.

---

Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.

Produktdetails

• Verlag: Springer New York
• Seitenzahl: 198
• Erscheinungstermin: 6. August 2007
• Englisch
• ISBN-13: 9780387728254
• Artikelnr.: 37286083

Autorenporträt

Stephen Fienberg, Carnegie-Mellon University, Pittsburgh, PA, USA

Inhaltsangabe

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 Zeros.

Rezensionen

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)