Download or read book Focused Multidimensional Scaling written by Lea M. Urpa and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Fundamentals of Applied Multidimensional Scaling for Educational and Psychological Research written by Cody S. Ding and published by Springer. This book was released on 2018-04-09 with total page 197 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores the fundamentals of multidimensional scaling (MDS) and how this analytic method can be used in applied setting for educational and psychological research. The book tries to make MDS more accessible to a wider audience in terms of the language and examples that are more relevant to educational and psychological research and less technical so that the readers are not overwhelmed by equations. The goal is for readers to learn the methods described in this book and immediately start using MDS via available software programs. The book also examines new applications that have previously not been discussed in MDS literature. It should be an ideal book for graduate students and researchers to better understand MDS. Fundamentals of Applied Multidimensional Scaling for Educational and Psychological Research is divided into three parts. Part I covers the basic and fundamental features of MDS models pertaining to applied research applications. Chapters in this section cover the essential features of data that are typically associated with MDS analysis such as preference ration or binary choice data, and also looking at metric and non-metric MDS models to build a foundation for later discussion and applications in later chapters. Part II examines specific MDS models and its applications for education and psychology. This includes spatial analysis methods that can be used in MDS to test clustering effect of items and individual differences MDS model (INDSCAL). Finally, Part III focuses on new applications of MDS analysis in these research fields. These new applications consist of profile analysis, longitudinal analysis, mean-level change, and pattern change. The book concludes with a historical review of MDS development as an analytical method and a look to future directions.
Download or read book Applied Multidimensional Scaling and Unfolding written by Ingwer Borg and published by Springer. This book was released on 2018-05-16 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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).
Download or read book Multidimensional Scaling written by Joseph B. Kruskal and published by SAGE Publications. This book was released on 1978-01-01 with total page 100 pages. Available in PDF, EPUB and Kindle. Book excerpt: Outlines a set of techniques that enables a researcher to explore the hidden structure of large databases. These techniques use proximities to find a configuration of points that reflect the structure in the data.
Download or read book Mastering Data Analysis with R written by Gergely Daroczi and published by Packt Publishing Ltd. This book was released on 2015-09-30 with total page 397 pages. Available in PDF, EPUB and Kindle. Book excerpt: Gain sharp insights into your data and solve real-world data science problems with R—from data munging to modeling and visualization About This Book Handle your data with precision and care for optimal business intelligence Restructure and transform your data to inform decision-making Packed with practical advice and tips to help you get to grips with data mining Who This Book Is For If you are a data scientist or R developer who wants to explore and optimize your use of R's advanced features and tools, this is the book for you. A basic knowledge of R is required, along with an understanding of database logic. What You Will Learn Connect to and load data from R's range of powerful databases Successfully fetch and parse structured and unstructured data Transform and restructure your data with efficient R packages Define and build complex statistical models with glm Develop and train machine learning algorithms Visualize social networks and graph data Deploy supervised and unsupervised classification algorithms Discover how to visualize spatial data with R In Detail R is an essential language for sharp and successful data analysis. Its numerous features and ease of use make it a powerful way of mining, managing, and interpreting large sets of data. In a world where understanding big data has become key, by mastering R you will be able to deal with your data effectively and efficiently. This book will give you the guidance you need to build and develop your knowledge and expertise. Bridging the gap between theory and practice, this book will help you to understand and use data for a competitive advantage. Beginning with taking you through essential data mining and management tasks such as munging, fetching, cleaning, and restructuring, the book then explores different model designs and the core components of effective analysis. You will then discover how to optimize your use of machine learning algorithms for classification and recommendation systems beside the traditional and more recent statistical methods. Style and approach Covering the essential tasks and skills within data science, Mastering Data Analysis provides you with solutions to the challenges of data science. Each section gives you a theoretical overview before demonstrating how to put the theory to work with real-world use cases and hands-on examples.
Download or read book The User s Guide to Multidimensional Scaling written by Anthony Peter Macmillan Coxon and published by Heinemann Educational Publishers. This book was released on 1982 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Multidimensional preference scaling written by Gordon G. Bechtel and published by Walter de Gruyter GmbH & Co KG. This book was released on 2019-05-20 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: No detailed description available for "Multidimensional preference scaling".
Download or read book Applied Multidimensional Scaling written by Ingwer Borg and published by Springer Science & Business Media. This book was released on 2012-10-30 with total page 119 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Multidimensional Scaling written by Forrest W. Young and published by Psychology Press. This book was released on 2013-05-13 with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt: This outstanding presentation of the fundamentals of multidimensional scaling illustrates the applicability of MDS to a wide variety of disciplines. The first two sections provide ground work in the history and theory of MDS. The final section applies MDS techniques to such diverse fields as physics, marketing, and political science.
Download or read book Three Way Scaling written by Phipps Arabie and published by SAGE. This book was released on 1987 with total page 100 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume is a logical extension of #11, Multidimensional Scaling, providing an up-to-date overview of some three-way modesl for multidimensional scaling and related techniques.104
Download or read book Practical Guide To Principal Component Methods in R written by Alboukadel KASSAMBARA and published by STHDA. This book was released on 2017-08-23 with total page 171 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although there are several good books on principal component methods (PCMs) and related topics, we felt that many of them are either too theoretical or too advanced. This book provides a solid practical guidance to summarize, visualize and interpret the most important information in a large multivariate data sets, using principal component methods in R. The visualization is based on the factoextra R package that we developed for creating easily beautiful ggplot2-based graphs from the output of PCMs. This book contains 4 parts. Part I provides a quick introduction to R and presents the key features of FactoMineR and factoextra. Part II describes classical principal component methods to analyze data sets containing, predominantly, either continuous or categorical variables. These methods include: Principal Component Analysis (PCA, for continuous variables), simple correspondence analysis (CA, for large contingency tables formed by two categorical variables) and Multiple CA (MCA, for a data set with more than 2 categorical variables). In Part III, you'll learn advanced methods for analyzing a data set containing a mix of variables (continuous and categorical) structured or not into groups: Factor Analysis of Mixed Data (FAMD) and Multiple Factor Analysis (MFA). Part IV covers hierarchical clustering on principal components (HCPC), which is useful for performing clustering with a data set containing only categorical variables or with a mixed data of categorical and continuous variables.
Download or read book Handbook of Applied Multivariate Statistics and Mathematical Modeling written by Howard E.A. Tinsley and published by Academic Press. This book was released on 2000-05-22 with total page 751 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multivariate statistics and mathematical models provide flexible and powerful tools essential in most disciplines. Nevertheless, many practicing researchers lack an adequate knowledge of these techniques, or did once know the techniques, but have not been able to keep abreast of new developments. The Handbook of Applied Multivariate Statistics and Mathematical Modeling explains the appropriate uses of multivariate procedures and mathematical modeling techniques, and prescribe practices that enable applied researchers to use these procedures effectively without needing to concern themselves with the mathematical basis. The Handbook emphasizes using models and statistics as tools. The objective of the book is to inform readers about which tool to use to accomplish which task. Each chapter begins with a discussion of what kinds of questions a particular technique can and cannot answer. As multivariate statistics and modeling techniques are useful across disciplines, these examples include issues of concern in biological and social sciences as well as the humanities.
Download or read book Metric Scaling written by Susan C. Weller and published by SAGE. This book was released on 1990 with total page 100 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presents a set of closely related techniques that facilitate the exploration and display of a wide variety of multivariate data, both categorical and continuous. Three methods of metric scaling, correspondence analysis, principal components analysis, and multiple dimensional preference scaling are explored in detail for strengths and weaknesses over a wide range of data types and research situations. "The introduction illustrates the methods with a small dataset. This approach is effective--in a few minutes, with no mathematical requirement, the reader can understand the capabilities, similarities, and differences of the methods. . . . Numerical examples facilitate learning. The authors use several examples with small datasets that illustrate very well the links and the differences between the methods. . . . we find this text very good and recommend it for graduate students and social science researchers, especially those who are interested in applying some of these methods and in knowing the relationship among them." --Journal of Marketing Research "Illustrate[s] the service Sage provides by making high-quality works on research methods available at modest prices. . . . The authors use several interesting examples of practical applications on data sets, ranging from contraception preferences, to pottery shards from archeological digs, to durable consumer goods from market research. These examples indicate the broad range of possible applications of the method to social science data." --Contemporary Sociology "The book is a bargain; it is clearly written." --Journal of Classification
Download or read book Modern Multidimensional Scaling written by Ingwer Borg and published by Springer Science & Business Media. This book was released on 2013-04-18 with total page 469 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multidimensional scaling (MDS) is a technique for the analysis of similarity or dissimilarity data on a set of objects. Such data may be intercorrelations of test items, ratings of similarity on political candidates, or trade indices for a set of countries. MDS attempts to model such data as distances among points in a geometric space. The main reason for doing this is that one wants a graphical display of the structure of the data, one that is much easier to understand than an array of numbers and, moreover, one that displays the essential information in the data, smoothing out noise. There are numerous varieties of MDS. Some facets for distinguishing among them are the particular type of geometry into which one wants to map the data, the mapping function, the algorithms used to find an optimal data representation, the treatment of statistical error in the models, or the possibility to represent not just one but several similarity matrices at the same time. Other facets relate to the different purposes for which MDS has been used, to various ways of looking at or "interpreting" an MDS representation, or to differences in the data required for the particular models. In this book, we give a fairly comprehensive presentation of MDS. For the reader with applied interests only, the first six chapters of Part I should be sufficient. They explain the basic notions of ordinary MDS, with an emphasis on how MDS can be helpful in answering substantive questions.
Download or read book Multidimensional Scaling written by Kruskal, Joseph B. and published by . This book was released on 1953 with total page 93 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Scaling Methods written by Peter Dunn-Rankin and published by Psychology Press. This book was released on 2014-04-04 with total page 283 pages. Available in PDF, EPUB and Kindle. Book excerpt: Scaling Methods is written for professionals in the behavioral sciences who analyze data that results from subjective responses. Other books on scaling attitudes or measuring perceptions focus on the psychometrician's view of measurement. This book focuses on the users' view by concentrating on effective ways to analyze data rather than the mathematical details of how each program works. The methods included handle the majority of data analysis problems encountered and are accompanied by a software solution. Each chapter features the theory surrounding that methodology, an example, a real-world application, and a computer solution. This book introduces the major uni- and multi-dimensional scaling method techniques most common in educational, social, and psychological research. Using four primary methods of data collection--ordering, categorical rating, free clustering, and similarity judgments--Scaling Methods, Second Edition explains how such data can be represented in ways that illustrate relationships among the data and help reveal underlying dimensional structures. Each method serves as an independent unit so readers can pick and choose from a variety of easy-to-use procedures and more advanced techniques. The new edition features a new chapter on order analysis and downloadable resources that provide stand-alone, as well as SAS supported demonstrations of multi-dimensional scaling techniques, plus programs to get raw data into matrix form. The text is written for researchers, practitioners, and advanced students in education and the social and behavioral sciences interested in analyzing data resulting from subjective responses, especially in the measurement of attitudes. Each chapter is self-contained making this an excellent resource for use in the classroom or as a self-study tool. A first course in statistics is a helpful prerequisite.
Download or read book Modern Multidimensional Scaling written by Ingwer Borg and published by Springer Verlag. This book was released on 1997-01-01 with total page 471 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive treatment of multidimensional scaling (MDS), a statistical technique used to analyze the structure of similarity or dissimilarity data in multidimensional space. There are many examples of such data, including intercorrelations of attitude items, direct ratings of similarity on choice objects, and trade indices for a set of countries. MDS models such data as distances between points in a geometric space of low dimensionality. This makes complex data sets accessible to visual exploration and thus makes it easier to see structure not obvious from the numbers. Other uses of MDS interpret the geometry and, in particular, the distance function as a psychological composition rule. The book may be used as an introduction to MDS for students in many areas, including statistics, psychology, sociology, political science, and marketing. The prerequisite is a two-semester course in statistics for the social or managerial sciences. The volume is also suited for various advanced courses on MDS, either with an emphasis on data analysis or a focus on the psychology of similarity. All the mathematics required for more advanced topics is developed systematically.
