1. Multivariate Data AnalysisChapter 10 - Multidimensional Scaling MIS 6093 Statistical Method Instructor: Dr. Ahmad Syamil

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. Chapter 10A 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. Chapter 10A 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. Chapter 10A 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. Chapter 10A 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. Chapter 10Correspondence 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 Analysis

8. Chapter 10Correspondence 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. Chapter 10Illustration 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. Chapter 10Illustration 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. Chapter 10Illustration 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

12. Chapter 10 • Summary • Questions • References ……end