Statistical Methods for Categorical Data Analysis is designed as an accessible reference work and textbook about categorical data (that is, data arising from counts instead of measurement. Examples include data about birth, death, marriage, and so forth). It integrates statistical and econometric approaches to the analysis of limited and categorical dependent variables, thereby offering a practical, mathematically uncomplicated approach to the topics of modern data analysis. The volume offers a comprehensive presentation of many different models in a one-volume format (with website).
Two features distinguish this book from other analyses of categorical data. First, the authors present both the transformational and latent variable approaches and so synthesize similar methods in statistical and econometric literatures. Second, the book has an applied orientation and features actual examples from social science research. The authors keep discussions of theory to a minimum.

Key Features
* Exercises and examples utilize popular data already familiar to many social scientists
* Examples of the use of various popular software packages
* Includes non-standard applications of existing software for estimating models which cannot be handled directly using existing pre-programmed software

About the Author

Yu Xie is John Stephenson Perrin Professor of Sociology and Associate Director of the Population Studies Center at the University of Michigan. He received his Ph.D. from the University of Wisconsin, Madison, and has received numerous awards for his scholarship and teaching.

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