Statistical science's first coordinated manual of methods for analyzing ordered categorical data presents applications and case studies in fields as diverse as sociology, public health, ecology, marketing, and pharmacy. Analysis of Ordinal Categorical Data provides an introduction to basic descriptive and inferential methods for categorical data and gives thorough coverage of late developments. Special emphasis is placed on interpretation and application of methods including an integrated comparison of the available strategies for analyzing ordinal data. The book also discusses implementation of methods using computer packages such as SAS, SPSSx, and GLIM.
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About the author Alan Agresti is an associate professor in the Department of Statistics at the University of Florida. Since receiving his PhD at the University of Wisconsin in 1972, he has published in many professional journals, including Journal of the American Statistical Association, Journal of the Royal Statistical Society, Biometrics, Journal of Applied Probability, Psychometrika, and Sociological Methodology. He is author of the text Statistical Methods for the Social Sciences and is an associate editor of The American Statistician.
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gebundene Ausgabe. Etat : Gut. 287 Seiten Das hier angebotene Buch stammt aus einer teilaufgelösten Bibliothek und kann die entsprechenden Kennzeichnungen aufweisen (Rückenschild, Instituts-Stempel.); der Buchzustand ist ansonsten ordentlich und dem Alter entsprechend gut. Original-Schutzumschlag vorhanden (siehe Foto). In ENGLISCHER Sprache. Sprache: Englisch Gewicht in Gramm: 605. N° de réf. du vendeur 2159144
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Vendeur : Dorley House Books, Inc., Hagerstown, MD, Etats-Unis
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Vendeur : Dorley House Books, Inc., Hagerstown, MD, Etats-Unis
Hardcover. Etat : Near Fine. Etat de la jaquette : Near Fine. 1st. 1st printing; dj in mylar; black c w/gilt titles on red; 287 clean, unmarked pages. focuses on statistical methods for variables with ranked categories (e.g., survey scales, education levels) where the ordering matters but distances between categories are unknown. It uses specialized models?such as cumulative logits, proportional odds models, and association models?to efficiently analyze ordered structures, often providing more power than nominal methods. N° de réf. du vendeur 1253573
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