Quantification methodology of categorical data is a popular topic in many branches of science. Most books, however, are either too advanced for those who need it, or too elementary to gain insight into its potential. This book fills the gap between these extremes, and provides specialists with an easy and comprehensive reference, and others with a complete treatment of dual scaling methodology -- starting with motivating examples, followed by an introductory discussion of necessary quantitative skills, and ending with different perpsectives on dual scaling with examples, advanced topics, and future possibilities.
This book attempts to successively upgrade readers' readiness for handling analysis of qualitative, categorical, and non-metric data, without overloading them. The writing style is very friendly, and difficult topics are always accompanied by simple illlustrative examples.
There are a number of topics on dual scaling which were previously addressed only in journal articles or in publications that are not readily available. Integration of these topics into the standard framework makes the current book unique, and its extensive coverage of relevant topics is unprecedented. This book will serve as both reference and textbook for all those who want to analyze categorical data effectively.
Table of Contents
Contents: Preface. Part I: Background. To Begin With. What Can Dual Scaling Do for You? Is Your Data Set Appropriate for Dual Scaling? Some Fundamentals for Dual Scaling. Useful Quantitative Tools. Mathematics of Dual Scaling. Part II: Incidence Data. Contingency/Frequency Tables. Multiple-Choice Data. Sorting Data. Part III: Dominance Data. Paired Comparison Data. Rank-Order Data. Successive Categories (Rating) Data. Part IV: Special Topics. Forced Classification and Focused Analysis. Graphical Display. Outliers and Missing Responses in Multiple-Choice Data. Analysis of Multiway Data. Additional Topics and Future Possibilities.
"...provides an accessible and practical discussion of dual scaling that should be useful to people in many fields."
"This is a useful book for both academic and industry marketing researchers. It contains extensions of correspondence analysis in clear and simple exposition that cannot be found elsewhere."
—Journal of Marketing Research
"The book is lucidly written, and provides an excellent text for a one-semester course on dual scaling at an advanced undergraduate or graduate level. Indeed, a copy of the book arrived when I was teaching dual scaling in my scaling course last year, and I could not help but immediately borrow several examples of applications from this book."
—Applied Psychological Measurement
"The persistent reader will be rewarded with insights into data analysis. Infact, (s)he will benefit from the book, even having only a vague understanding of the mathematical details of the technique. The main reason for this is Nishisato's taking the time to explain the problems and the solutions in sufficient detail."
—Canadian Journal of Marketing Research
"...contains many examples and data sets and these are discussed at length. For teaching purposes this would be useful."
"The author has assembled a great deal of information on the application of dual scaling to categorical data. This book should be valuable to anyone dealing with survey questionnaire data, particularly multiple-choice survey data."
—Journal of Classification