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Table of Contents
Intro; Preface; Contents; 1 First Steps; 1.1 Basic Ideas of Multidimensional Scaling; 1.2 Basic Ideas of Unfolding; 1.3 Summary; References; 2 The Purpose of MDS and Unfolding; 2.1 MDS for Visualizing Proximity Data; 2.2 MDS for Uncovering Latent Dimensions of Judgment; 2.3 Distance Formulas as Models of Judgment; 2.4 MDS for Testing Structural Hypotheses; 2.5 Unfolding as a Psychological Model of Preference; 2.6 Summary; References; 3 The Fit of MDS and Unfolding Solutions; 3.1 The Global Stress of MDS Solutions; 3.2 Evaluating Stress Statistically; 3.3 Stress and MDS Dimensionality
3.4 Stress Per Point3.5 Conditions Causing High Stress in MDS; 3.6 Stress in Unfolding; 3.7 Stability of MDS Solutions; 3.8 Summary; References; 4 Proximities; 4.1 Direct Proximities; 4.2 Derived Proximities; 4.3 Proximities from Index Conversions; 4.4 Co-occurrence Data; 4.5 The Gravity Model for Co-occurrences; 4.6 Summary; References; 5 Variants of MDS Models; 5.1 The Type of Regression in MDS; 5.2 Euclidean and Other Distances; 5.3 MDS of Asymmetric Proximities; 5.4 Modeling Individual Differences in MDS; 5.5 Scaling Replicated Proximities; 5.6 Weighting Proximities in MDS; 5.7 Summary
7.8 Always Interpreting Principal Axes Dimensions7.9 Always Interpreting Dimensions or Directions; 7.10 Poorly Dealing with Disturbing Points; 7.11 Scaling Almost-Equal Proximities; 7.12 Summary; References; 8 Unfolding; 8.1 Unfolding in Three-Dimensional Space; 8.2 Multidimensional Versus Multiple Unfolding; 8.3 Conditionalities in Unfolding; 8.4 Stability of Unfolding Solutions; 8.5 Degenerate Unfolding Solutions; 8.6 Special Unfolding Models; 8.7 Summary; References; 9 MDS Algorithms; 9.1 Classical MDS; 9.2 Iterative MDS Algorithms; 9.3 Summary; References; 10 MDS Software; 10.1 Proxscal
10.2 The R Package smacof10.2.1 Functions in smacof; 10.2.2 A Simple MDS Example; References; Index
3.4 Stress Per Point3.5 Conditions Causing High Stress in MDS; 3.6 Stress in Unfolding; 3.7 Stability of MDS Solutions; 3.8 Summary; References; 4 Proximities; 4.1 Direct Proximities; 4.2 Derived Proximities; 4.3 Proximities from Index Conversions; 4.4 Co-occurrence Data; 4.5 The Gravity Model for Co-occurrences; 4.6 Summary; References; 5 Variants of MDS Models; 5.1 The Type of Regression in MDS; 5.2 Euclidean and Other Distances; 5.3 MDS of Asymmetric Proximities; 5.4 Modeling Individual Differences in MDS; 5.5 Scaling Replicated Proximities; 5.6 Weighting Proximities in MDS; 5.7 Summary
7.8 Always Interpreting Principal Axes Dimensions7.9 Always Interpreting Dimensions or Directions; 7.10 Poorly Dealing with Disturbing Points; 7.11 Scaling Almost-Equal Proximities; 7.12 Summary; References; 8 Unfolding; 8.1 Unfolding in Three-Dimensional Space; 8.2 Multidimensional Versus Multiple Unfolding; 8.3 Conditionalities in Unfolding; 8.4 Stability of Unfolding Solutions; 8.5 Degenerate Unfolding Solutions; 8.6 Special Unfolding Models; 8.7 Summary; References; 9 MDS Algorithms; 9.1 Classical MDS; 9.2 Iterative MDS Algorithms; 9.3 Summary; References; 10 MDS Software; 10.1 Proxscal
10.2 The R Package smacof10.2.1 Functions in smacof; 10.2.2 A Simple MDS Example; References; Index