Overview
- Provides a concise, largely conceptual introduction to multidimensional scaling and unfolding
- Focuses on how to actually run and interpret MDS and unfolding in applied research (with examples from psychology, the social sciences, and market research)
- Explains with several examples how to use the R-package smacof for MDS/unfolding and Proxscal in SPSS
- Includes numerous R-scripts that show how to run MDS and unfolding analyses (a file containing all scripts, and more, can be downloaded)
Part of the book series: SpringerBriefs in Statistics (BRIEFSSTATIST)
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About this book
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.).
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Table of contents (10 chapters)
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Authors and Affiliations
About the authors
Ingwer Borg is visiting professor of psychology at WWU Münster (Germany). He was scientific director at GESIS (Mannheim, Germany), psychology professor at JLU (Gießen, Germany), and research director at HRC (Munich, Germany). He has authored or edited 20 books and numerous articles on data analysis, survey research, theory construction, and various substantive fields of psychology, from psychophysics to job satisfaction.
Patrick J.F. Groenen is professor of statistics at the Econometric Institute, Erasmus University Rotterdam, the Netherlands. His main research interests are in data science visualization techniques, such as multidimensional scaling, unfolding, and nonlinear multivariate analysis techniques. He has coauthored both technical and more applied papers in a variety of international journals.
Patrick Mair received his PhD in statistics from the University of Vienna in 2005. Since 2013 he has worked as senior lecturer in statistics at the Department ofPsychology, Harvard University. His research focuses on computational and applied statistics with special emphasis on psychometric methods, such as latent variable models and multivariate exploratory techniques.
Bibliographic Information
Book Title: Applied Multidimensional Scaling and Unfolding
Authors: Ingwer Borg, Patrick J.F. Groenen, Patrick Mair
Series Title: SpringerBriefs in Statistics
DOI: https://doi.org/10.1007/978-3-319-73471-2
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: The Author(s) 2018
Softcover ISBN: 978-3-319-73470-5Published: 25 May 2018
eBook ISBN: 978-3-319-73471-2Published: 16 May 2018
Series ISSN: 2191-544X
Series E-ISSN: 2191-5458
Edition Number: 2
Number of Pages: IX, 122
Number of Illustrations: 65 b/w illustrations
Topics: Statistics and Computing/Statistics Programs, Psychometrics, Statistics for Social Sciences, Humanities, Law, Statistics for Life Sciences, Medicine, Health Sciences, Visualization, Computational Social Sciences