Outlines a set of techniques that enable a researcher to discuss the "hidden structure" of large data bases. These techniques use proximities, measures which indicate how similar or different objects are, to find a configuration of points which reflects the structure in the data.
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Most Helpful Customer Reviews
14 of 15 people found the following review helpful:
5.0 out of 5 stars
Excellent layman's introduction to Multi-Dimensional Scaling,
By Scott Lake (scorae@juno.com) (Waterford, Michigan, USA) - See all my reviews
This review is from: Multidimensional Scaling (Quantitative Applications in the Social Sciences) (Paperback)
This book is an excellent layman's introduction to the topic of Multi-Dimensional Scaling (MDS). There is just the right amount of detail to quickly get started in practical use of MDS. Some of the data and projects in this text are used as examples in StatSoft's Statistica software for PC's and Mac's; establishing a much needed connection between a reference text and software that incorporates the mathematics in the topic.
7 of 7 people found the following review helpful:
5.0 out of 5 stars
An MDS monograph written for applied researchers,
By VONG TZE NGAI (Macau SAR, China (louis@ift.edu.mo)) - See all my reviews
This review is from: Multidimensional Scaling (Quantitative Applications in the Social Sciences) (Paperback)
It is quite hard to find easy-reading reference for MDS. Some are written in Mathematics rather than in English. Others are over comprehensive as an introductory text for laymen. In this regard, I found Kruskal and Wish's "Multidimensional Scaling" to be the most 'user friendly'( only in a relative sense). In short, this is certainly a monograph with just the right amount of substances for any applied researcher interested in MDS to get started with their work. Fundamental knowledge of statistics is a prerequisite, of course.
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Inside This Book
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First Sentence:
Suppose you are given a map showing the locations of several cities in the United States, and are asked to construct a table of distances between these cities (see Figures 1A and 1B). Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
group stimulus space, profile proximities, nonmetric scaling, appropriate dimensionality, proximity matrix, proximities data, nonmetric multidimensional scaling, profile distances, similarity ratings, dimensional interpretation Key Phrases - Capitalized Phrases (CAPs): (learn more)
Monte Carlo, Latin American, Matrices of Similarities New!
Books on Related Topics | Concordance | Text Stats Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Back Cover | Surprise Me!
Suppose you are given a map showing the locations of several cities in the United States, and are asked to construct a table of distances between these cities (see Figures 1A and 1B). Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
group stimulus space, profile proximities, nonmetric scaling, appropriate dimensionality, proximity matrix, proximities data, nonmetric multidimensional scaling, profile distances, similarity ratings, dimensional interpretation Key Phrases - Capitalized Phrases (CAPs): (learn more)
Monte Carlo, Latin American, Matrices of Similarities New!
Books on Related Topics | Concordance | Text Stats Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Back Cover | Surprise Me!
Citations (learn more)
This book cites 72
books:
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100
books
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- A Theory of Data by Clyde Hamilton Coombs in Back Matter
- The Psychology of Personal Constructs: Volume Two: Clinical Diagnosis and Psychotherapy by George Kelly in Back Matter
- Causal Modeling (Quantitative Applications in the Social Sciences) by Herbert B. Asher in Back Matter
- Analyzing Panel Data (Quantitative Applications in the Social Sciences) by Gregory B. Markus in Back Matter
- Stochastic Parameter Regression Models (Quantitative Applications in the Social Sciences) by Paul Newbold in Back Matter
See all 72 books this book cites
- Data Theory and Dimensional Analysis (Quantitative Applications in the Social Sciences) by William G. Jacoby on 5 pages
- Three Way Scaling: A Guide to Multidimensional Scaling and Clustering (Quantitative Applications in the Social Sciences) by Phipps Arabie on 4 pages
- Typologies and Taxonomies: An Introduction to Classification Techniques (Quantitative Applications in the Social Sciences) by Kenneth D. Bailey on page 71, Back Matter (1), and Back Matter (2)
- Visualization of Categorical Data by Jörg Blasius on page 346, Back Matter (1), and Back Matter (2)
- Multivariate Analysis: Methods and Applications (Wiley Series in Probability and Statistics) by William R. Dillon in Back Matter (1), and Back Matter (2)
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