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Applied Multidimensional Scaling and Unfolding (Paperback, 2nd ed. 2018)
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Applied Multidimensional Scaling and Unfolding (Paperback, 2nd ed. 2018)
Series: SpringerBriefs in Statistics
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This book introduces multidimensional scaling (MDS) and unfolding
as data analysis techniques for applied researchers. MDS is used
for the analysis of proximity data on a set of objects,
representing the data as distances between points in a geometric
space (usually of two dimensions). Unfolding is a related method
that maps preference data (typically evaluative ratings of
different persons on a set of objects) as distances between two
sets of points (representing the persons and the objects, resp.).
This second edition has been completely revised to reflect new
developments and the coverage of unfolding has also been
substantially expanded. Intended for applied researchers whose main
interests are in using these methods as tools for building
substantive theories, it discusses numerous applications (classical
and recent), highlights practical issues (such as evaluating model
fit), presents ways to enforce theoretical expectations for the
scaling solutions, and addresses the typical mistakes that
MDS/unfolding users tend to make. Further, it shows how MDS and
unfolding can be used in practical research work, primarily by
using the smacof package in the R environment but also Proxscal in
SPSS. It is a valuable resource for psychologists, social
scientists, and market researchers, with a basic understanding of
multivariate statistics (such as multiple regression and factor
analysis).
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