This book introduces MDS as a psychological model and as a data analysis technique for the applied researcher. It also discusses, in detail, how to use two MDS programs, Proxscal (a module of SPSS) and Smacof (an R-package). The book is unique in its orientation on the applied researcher, whose primary interest is in using MDS as a tool to build substantive theories. This is done by emphasizing practical issues (such as evaluating model fit), by presenting ways to enforce theoretical expectations on the MDS solution, and by discussing typical mistakes that MDS users tend to make. The primary audience of this book are psychologists, social scientists, and market researchers. No particular background knowledge is required, beyond a basic knowledge of statistics.
Series
Edition
Language
Place of publication
Publishing group
Target group
Professional and scholarly
Research
Illustrations
59 s/w Abbildungen
59 Illustrations, black and white; IX, 113 p. 59 illus.
Dimensions
Height: 23.5 cm
Width: 15.5 cm
Weight
ISBN-13
978-3-642-31847-4 (9783642318474)
DOI
10.1007/978-3-642-31848-1
Schweitzer Classification
Ingwer Borg
is a Professor Emeritus at GESIS - Leibniz Institute for the Social Sciences, Mannheim, Germany. He has authored or edited 18 books and numerous academic articles on scaling, data analysis, survey research, theory construction, and various substantive topics of psychology. He has also served as president of several professional organizations.
Patrick J. F. Groenen
is a Professor of Statistics at the Econometric Institute, Erasmus University Rotterdam, The Netherlands. He has written several books and authored over 40 academic articles on topics including multidimensional scaling, multivariate analysis, classification, and visualization.
Patrick Mair
is an Adjunct Professor at the Department of Statistics and Mathematics, WU Vienna University of Economics and Business. His research focuses on applied and computational statistics, with a special emphasis on psychometric methods.
First Steps.- The Purpose of MDS.- The Goodness of an MDS Solution.- Proximities.- Variants of Different MDS Models.- Confirmatory MDS.- Typical Mistakes in MDS.- MDS Algorithms.- Computer Programs for MDS.
