Page 304 - DMGT404 RESEARCH_METHODOLOGY

Research Methodology

Notes

Notes Similarities and Differences between Factor Analysis and MDS
We have already seen that MDS can accept more different measures of similarity and
dissimilarity than factor analysis techniques can. In addition, there are some differences in
terminology. These differences reflect the origin of MDS in the field of psychology. The
measure corresponding to factors are called alternatively dimensions or stimulus
coordinates.
The output of MDS looks very similar to that of factor analysis and the determination of
the optimal number of dimensions is handled in much the same way.

Steps in using MDS

There are four basic steps in MDS:
1. Data collection and formation of the similarity/dissimilarity matrix
2. Extraction of stimulus coordinates
3. Decision about the number of stimulus coordinates that represent the data

4. Rotation and interpretation

Example: Let us say that you have a matrix of distances between a number of major cities,
such as you might find on the back of a road map. These distances can be used as the input data
to derive an MDS solution. When the results are mapped in two dimensions, the solution will
reproduce a conventional map, except that the MDS plot might need to be rotated so that the
north-south and east-west dimensions conform to expectations. However, the once the rotation
is completed, the configuration of the cities will be spatially correct.

Self Assessment

Fill in the blanks:
14. An advantage of the non-metric models is that they permit the researcher to .......................
and ....................... preference data.
15. The spatial display of data provided by MDS is also sometimes referred to as ………………..

13.7 Summary

 Multivariate analysis is used if there are more than 2 variables.
 Some of the multi variate analysis are discriminant analysis, Factor analysis, Cluster
analysis, conjoint analysis, and multi dimensional scaling.

 In discriminant analysis, it is verified whether the 2 groups differ from one another.
 Factor analysis is used to reduce large no of various factors into fewer variables cluster
analysis is used to segmenting the market or to identify the target group.

 Regression is a term used for predicting the value of one variable from the other.
 Least square method is used to fit the line.

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