Article Fingerprint
ReserarchID
63P51
Perceptual mapping is widely spread to assess perception in different areas, like marketing, political and social sciences, psychology and others. One opportunity for development is to add statistical inference on final configuration in order to consider inherent differences of a group of evaluators. The main objective is to produce multiple perceptual maps from focal panel and to incorporate the confidence regions of different evaluators into the visual representation using MDSvarext. The algorithm represents a joining of non metric multidimensional scaling, shape statistical tool, clustering techniques and non parametric estimation of variance-covariance matrix to generate a visual representation of object’s perception and its confidence regions. An experiment to assess occupational risk perception has been run in order to demonstrate the method. The results showed that different perceptual maps are needed to encompass the variability of a focal group. The generated perceptual maps have different interpretations since the objects may be on opposite sides of the graph. The solution generated by MDsvarext was effective and statistical inference could be done. To explore the variability in focal groups is very important, and MDSvarext represents a path to be followed, since it was possible to visualize the differences that are statistical significant.
Moacyr Machado Cardoso Junior. 2014. \u201cMultiple Perceptual Map Generation using MDSvarext\u201d. Global Journal of Research in Engineering - J: General Engineering GJRE-J Volume 14 (GJRE Volume 14 Issue J3): .
Crossref Journal DOI 10.17406/gjre
Print ISSN 0975-5861
e-ISSN 2249-4596
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Total Score: 102
Country: Brazil
Subject: Global Journal of Research in Engineering - J: General Engineering
Authors: Moacyr Machado Cardoso Junior, Rodrigo Arnaldo Scarpel (PhD/Dr. count: 0)
View Count (all-time): 213
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Publish Date: 2014 09, Thu
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Perceptual mapping is widely spread to assess perception in different areas, like marketing, political and social sciences, psychology and others. One opportunity for development is to add statistical inference on final configuration in order to consider inherent differences of a group of evaluators. The main objective is to produce multiple perceptual maps from focal panel and to incorporate the confidence regions of different evaluators into the visual representation using MDSvarext. The algorithm represents a joining of non metric multidimensional scaling, shape statistical tool, clustering techniques and non parametric estimation of variance-covariance matrix to generate a visual representation of object’s perception and its confidence regions. An experiment to assess occupational risk perception has been run in order to demonstrate the method. The results showed that different perceptual maps are needed to encompass the variability of a focal group. The generated perceptual maps have different interpretations since the objects may be on opposite sides of the graph. The solution generated by MDsvarext was effective and statistical inference could be done. To explore the variability in focal groups is very important, and MDSvarext represents a path to be followed, since it was possible to visualize the differences that are statistical significant.
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