Posted April 2, 2012 by Team AnalyticpediA in Analytics

Multidimensional Scaling (MDS)

Multi Dimensional Scaling
Multi Dimensional Scaling


Multidimensional scaling (MDS) provides the researcher with a spatial representation of data that can facilitate interpretation and reveal relationships. Therefore, we can define MDS as “a set of multivariate statistical methods for estimating the parameters in and assessing the fit of various spatial distance models for proximity data” . The spatial display of data provided by MDS is why it is also sometimes referred to as perceptual mapping. MDS has much more flexibility about the types of data that can be used to generate the solution. Almost any measures of similarity and dissimilarity can be used, depending on what your statistical computer software will accept.

 Types of MDS

In general, there are two types of MDS:

1. Metric

2. Non-metric

Metric MDS makes the assumption that the input data is either ratio or interval data, while the non-metric model requires simply that the data be in the form of ranks. Therefore, the non-metric model has more fewer restrictions than the metric model, but also less rigor. One technique to use if you are unsure whether your data is ordinal or can be considered interval is to try both metric and non-metric models. If the results are very close, the metric model may be used.
An advantage of the non-metric models is that they permit the researcher to categorize and examine preference data, such as the kind obtained in marketing studies or other areas where comparisons are useful.

Steps in using MDS

There are four basic steps in MDS:

  • Data collection and formation of the similarity/dissimilarity matrix
  • Extraction of stimulus coordinates
  • Decision about the number of stimulus coordinates that represent the data
  • Rotation and interpretation

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