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作者 Borg, Ingwer, author
書名 Applied multidimensional scaling and unfolding / by Ingwer Borg, Patrick J. F. Groenen, Patrick Mair
出版項 Cham : Springer International Publishing : Imprint: Springer, 2018
國際標準書號 9783319734712 (electronic bk.)
9783319734705 (paper)
國際標準號碼 10.1007/978-3-319-73471-2 doi
book jacket
版本 Second edition
說明 1 online resource (ix, 122 pages) : digital ; 24 cm
text txt rdacontent
computer c rdamedia
online resource cr rdacarrier
text file PDF rda
系列 SpringerBriefs in statistics, 2191-544X
SpringerBriefs in statistics
附註 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)
Host Item Springer eBooks
主題 Multidimensional scaling
Statistics and Computing/Statistics Programs
Statistics for Social Science, Behavorial Science, Education, Public Policy, and Law
Statistics for Life Sciences, Medicine, Health Sciences
Computational Social Sciences
Alt Author Groenen, Patrick J. F., author
Mair, Patrick, author
SpringerLink (Online service)
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