|aStatistical methods for categorical data analysis /|cDaniel A. Powers, Yu Xie.
|aBingley, UK :|bEmerald,|c2008.
|axvii, 317 pages :|billustrations ;|c25 cm
|a"First edition [sic]"--Title page verso.
|aIncludes bibliographical references (pages 297-306) and index.
|aReview 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.
|a"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.