1. Multivariate Data Analysis Chapter 10 - Multidimensional Scaling

2. Chapter 10 What Is Multidimensional Scaling?
A Simplified Look at How Multidimensional Scaling Works
Comparing MDS to Other Interdependence Techniques
Individual As the Unit of Analysis
Lack of a Variate

3. A Decision Framework for Perceptual Mapping
Stage 1: Objectives of Multidimensional
Scaling
Key Decisions in Setting Objectives
Identification of All Relevant Objects to Be Evaluated
Similarities Versus Preference Data
Aggregate Versus Disaggregate Analysis

4. A Decision Framework for Perceptual Mapping (Cont.)
Stage 2: Research Design of Multidimensional Scaling
Selection of Either a Decompositional (Attribute-free) or Compositional (Attribute-based) Approach
Decompositional or Attribute-free Approach
Compositional or Attribute-based Approach
Selecting Between Compositional and Decompositional Techniques
Objects: Their Number and Selection
Nonmetric Versus Metric Methods
Collection of Similarity or Preference Data
Similarities Data
Comparison of Paired Objects
Confusion Data
Derived Measures
Collecting Preference Data
Direct Ranking
Paired Comparisons
Preference Data Versus Similarity Data

5. A Decision Framework for Perceptual Mapping (Cont.)
Stage 3: Assumptions of Multidimensional Scaling Analysis
Stage 4: Deriving the MDS Solution and Assessing Overall Fit
Determining an Object's Position in the Perceptual Map
Selecting the Dimensionality of the Perceptual Map
Incorporating Preferences into Multidimensional Scaling
Ideal Points
Positioning the Ideal Point
Internal Analysis
External Analysis
Vector Versus Point Representations
Summary

6. Decision Framework for Perceptual Mapping (Cont.)
Stage 5: Interpreting the MDS Results
Identifying the Dimensions
Subjective Procedures
Objective Procedures
Selecting Between Subjective and Objective Procedures
Stage 6: Validating the MDS Results

7. Correspondence Analysis
A Simple Example of Correspondence Analysis
Calculating A Measure of Association
Creating the Perceptual Map
Stage 1: Objectives of Correspondence Analysis
Stage 2: Research Design of Correspondence
Analysis
Stage 3: Assumptions in Correspondence

8. Correspondence Analysis (Cont.)
Stage 4: Deriving the Correspondence
Analysis Results and Assessing
Overall Fit
Stage 5: Interpretation of Results
Stage 6: Validation of the Results
Overview of Correspondence Analysis

9. Illustration of Multidimensional Scaling and Correspondence Analysis
Stage 1: Objectives of Perceptual Mapping
Stage 2: Research Design of the Perceptual
Mapping Study
Similarity Data
Attribute Ratings
Preference Evaluations
Stage 3: Assumptions in Perceptual Mapping

10. Multidimensional Scaling: Stages 4 and 5
Illustration of Multidimensional Scaling and Correspondence Analysis (Cont.)
Multidimensional Scaling: Stages 4 and 5
Stage 4: Deriving the Multidimensional Scaling Results and Assessing Overall Fit
Incorporating Preferences in the Perceptual Map
Stage 5: Interpretation of the Results
Overview of the Decompositional Results

11. Correspondence Analysis: Stages 4 and 5
Illustration of Multidimensional Scaling and Correspondence Analysis (Cont.)
Correspondence Analysis: Stages 4 and 5
Stage 4: Deriving the Correspondence Analysis
Stage 5: Interpreting the Correspondence
Analysis Results
An Overview of Correspondence Analysis
Stage 6: Validation of the Results
A Managerial Overview of the Multidimensional Scaling Results