Applied Multidimensional Scaling and Unfolding [[electronic resource] /] / by Ingwer Borg, Patrick J.F. Groenen, Patrick Mair

• Autore: Borg Ingwer
• Pubblicazione: Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018
• Edizione: 2nd ed. 2018.
• Descrizione fisica: 1 online resource (IX, 122 p. 65 illus.)
• Disciplina: 001.4226
• Soggetto topico: Statistics ; Psychometrics; Mathematics; Visualization; Social sciences—Data processing; Social sciences—Computer programs; Statistics and Computing/Statistics Programs; Statistics for Social Sciences, Humanities, Law; Statistics for Life Sciences, Medicine, Health Sciences; Computational Social Sciences
• Persona (resp. second.): GroenenPatrick J.F; MairPatrick
• Nota di contenuto: 1 First steps -- 2 The purpose of MDS and Unfolding -- 3 The fit of MDS and Unfolding solutions -- 4 Proximities -- 5 Variants of MDS models -- 6 Confirmatory MDS -- 7 Typical mistakes in MDS -- 8 Unfolding -- 9 MDS algorithms -- 10 MDS Software -- Subject Index.
• Sommario/riassunto: 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).
• Titolo autorizzato: Applied Multidimensional Scaling and Unfolding
• ISBN: 3-319-73471-7
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910300120503321
• Lo trovi qui: Univ. Federico II
• Serie: SpringerBriefs in Statistics, . 2191-544X