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Statistical methods for categorical data analysis / Daniel A. Powers, Yu Xie.

By: Contributor(s): Material type: TextTextPublisher: Bingley, UK : Emerald, 2008Edition: Second editionDescription: 1 online resource (xvii, 317 pages) : illustrationsContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781781906590
  • 1781906599
Subject(s): Genre/Form: Additional physical formats: Print version:: Statistical methods for categorical data analysis.DDC classification:
  • 519.535 22
LOC classification:
  • QA278 .P59 2008eb
Online resources:
Contents:
Review of linear regression models -- Models for binary data -- Loglinear models for contingency tables -- Multilevel models for binary data -- Statistical models for event occurrence -- Models for ordinal dependent variables -- Models for nominal dependent variables.
Review: "Statistical Methods for Categorical Data Analysis by Daniel A. Powers and Yu Xie provides a comprehensive introduction to methods and models for categorical data analysis and their applications in social science research. An explicit aim of the book is to integrate the transformational and the latent variable approach, two diverse but complementary traditions dealing with the analysis of categorical data. This is the first introductory text to cover models and methods for discrete dependent variables, cross-classifications, and longitudinal data in a rigorous, yet accessible, manner in a single volume." "This book presents the essential methods and models that form the core of contemporary social statistics. The book covers a remarkable range of models that have applications in sociology, demography, psychometrics, econometrics, political science, biostatistics, and other fields. It will be especially useful as a graduate textbook for students in advanced social statistics courses and as a reference book for applied researchers."--Jacket.
Holdings
Item type Current library Collection Call number Status Date due Barcode Item holds
eBook eBook e-Library EBSCO Mathematics Available
Total holds: 0

"First edition [sic]"--Title page verso.

Includes bibliographical references (pages 297-306) and index.

Review of linear regression models -- Models for binary data -- Loglinear models for contingency tables -- Multilevel models for binary data -- Statistical models for event occurrence -- Models for ordinal dependent variables -- Models for nominal dependent variables.

"Statistical Methods for Categorical Data Analysis by Daniel A. Powers and Yu Xie provides a comprehensive introduction to methods and models for categorical data analysis and their applications in social science research. An explicit aim of the book is to integrate the transformational and the latent variable approach, two diverse but complementary traditions dealing with the analysis of categorical data. This is the first introductory text to cover models and methods for discrete dependent variables, cross-classifications, and longitudinal data in a rigorous, yet accessible, manner in a single volume." "This book presents the essential methods and models that form the core of contemporary social statistics. The book covers a remarkable range of models that have applications in sociology, demography, psychometrics, econometrics, political science, biostatistics, and other fields. It will be especially useful as a graduate textbook for students in advanced social statistics courses and as a reference book for applied researchers."--Jacket.

Print version record.

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