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Elements of Dual Scaling : an Introduction To Practical Data Analysis.

Author: Shizuhiko Nishisato
Publisher: Hoboken : Taylor and Francis, 2014.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
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  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Nishisato, Shizuhiko.
Elements of Dual Scaling : An Introduction To Practical Data Analysis.
Hoboken : Taylor and Francis, ©2014
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Shizuhiko Nishisato
ISBN: 9781317781943 1317781945
OCLC Number: 876512792
Notes: 12.1.2 Treatment of Missing Responses.
Description: 1 online resource (398 pages)
Contents: Cover; Half Title; Title Page; Copyright Page; Dedication; Table of Contents; Preface; Part I Background; Chapter 1 To Begin With; Chapter 2 What Can Dual Scaling Do for You?; 2.1 Evaluating Teachers' Performance; 2.2 Gender, Age, and Suicides; 2.3 Highly Opinionated, and What Else?; 2.4 Some Characteristics of Dual Scaling; 2.5 Some Observations on Human Judgment; Chapter 3 Is Your Data Set ApproprIate for Dual Scaling?; 3.1 Exploratory Analysis and Data Types; 3.2 Contingency/Frequency Data; 3.3 Multiple-Choice Data; 3.3.1 Standard Form: Choosing One Option per Question. 3.3.2 Multiple-Response Form: Choosing More Than One Option per Question3.4 Paired Comparison Data; 3.5 Rank-Order Data; 3.6 Successive Categories (Rating) Data; 3.7 Sorting Data; 3.8 Categorized Continuous Data and Other Types of Categorical Data; 3.9 Multiway Data; 3.10 What If Your Data Set Is Not Appropriate for Dual Scaling?; 3.10.1 Principal Component Analysis (PCA) and Factor Analysis (FA); 3.10.2 Cluster Analysis (CL); 3.10.3 Nonmetric Multidimensional Scaling (MDS); 3.10.4 Analysis of Variance (ANOVA); 3.10.5 Regression Analysis (RA); 3.10.6 Canonical Analysis (CA). 3.10.7 Loglinear Analysis (LA)Chapter 4 Some Fundamentals for Dual Scaling; 4.1 Sum of Weighted Responses (Continuous Data); 4.2 Sum of Weighted Responses (Categorical Data); 4.3 Within and Between; 4.4 Duality and Guttman's Principle of Internal Consistency; 4.5 Correlation and Simultaneous Linear Regression; 4.6 Reciprocal Averaging; Chapter 5 Useful Quantitative Tools; 5.1 Simple Vector and Matrix Operations; 5.2 Canonical Reduction and Eigenequation; 5.3 Derivation of Eigenequation; 5.4 Finding the Maximal Eigenvalue; Chapter 6 Mathematics of Dual Scaling; 6.1 Optimal Solution. 6.2 Multidimensional Decomposition6.3 Some Interesting Relations; 6.4 Cautionary Notes on Joint Graphical Display; Part II Incidence Data; Chapter 7 Contingency/Frequency Tables; 7.1 Special Problems; 7.2 Applications; 7.2.1 Theory of Evolution?; 7.2.2 Rorschach Responses and Induced Moods; Chapter 8 Multiple-Choice Data; 8.1 Special Problems; 8.1.1 Relation Between Contingency Table and Multiple-Choice Data; 8.1.2 Number of Response Options; 8.1.3 Useful Statistics; 8.2 Applications; 8.2.1 Singapore Data; 8.2.2 As Compared with an Average Person; Chapter 9 Sorting Data; 9.1 Special Problems. 9.2 Applications9.2.1 Sorting 51 Car Models; 9.2.2 Classifying 39 Countries; Part III Dominance Data; Chapter 10 Paired Comparison Data; 10.1 Special Problems; 10.2 Applications; 10.2.1 Eight Christmas Party Plans; 10.2.2 Seriousness of Eight Crimes; Chapter 11 Rank-Order Data; 11.1 Special Problems; 11.1.1 Treatment of Incomplete Ranking and Missing Responses; 11.2 Applications; 11.2.1 Ranking of 10 Government Services; 11.2.2 Ranking of Eight Christmas Party Plans; Chapter 12 Successive Categories (Rating) Data; 12.1 Special Problems; 12.1.1 Basic Formulation.

Abstract:

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 f.

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