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Multivariate Methods > Multidimensional Scaling
Publication date: 04/21/2023

Multidimensional Scaling

Visualize Proximities among a Set of Objects

Multidimensional Scaling (MDS) is a technique that is used to create a visual representation of the pattern of proximities (similarities, dissimilarities, or distances) among a set of objects. For example, given a matrix of distances between cities, MDS can be used to generate a map of the cities in two dimensions.

Multidimensional Scaling is frequently used in consumer research where researchers have measures of perceptions about brands, tastes, or other product attributes. MDS is applicable to many other areas where one is interested in visualizing the proximity of objects based on a set of attributes or proximities.

Figure 10.1 Multidimensional Scaling Example 

Multidimensional Scaling Example

Contents

Overview of the Multidimensional Scaling Platform

Example of Multidimensional Scaling

Launch the Multidimensional Scaling Platform

The Multidimensional Scaling Report

Multidimensional Scaling Plot
Shepard Diagram
Fit Details

Multidimensional Scaling Platform Options

Waern Links

Additional Example of Multidimensional Scaling

Statistical Details for the Multidimensional Scaling Platform

Statistical Details for the Stress Function
Statistical Details for Transformations
Statistical Details for Attributes List Format
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