Value structure - On the use of weakly constrained confirmatory MDS : Paper presented at the 19th International Congress of the International Association for Cross-Cultural Psychology July 27-31, 2008, Bremen, Germany
Ordinal Multidimensional Scaling (MDS) has become a central approach for analyzing value structures in cross-cultural studies. Starting from regional hypotheses, MDS displays the discrimina-bility of value types in an easily accessible geometric represent-tation. Furthermore, this approach is relati...
|Division/Institute:||FB 07: Psychologie und Sportwissenschaft|
|Document types:||Working paper|
|Date of publication on miami:||23.07.2019|
|Series:||Berichte aus der Arbeitseinheit Differentielle Psychologie und Persönlichkeitspsychologie, Bd. 32|
|Edition statement:||[Electronic ed.]|
|Subjects:||value structure; weakly constrained confirmatory MDS; starting configuration; Computerized paired comparisons of values (CPCV); Portrait Values Questionnaire (PVQ40); European Social Survey (ESS)|
|DDC Subject:||150: Psychologie|
|Notes:||Berichte aus dem Psychologischen Institut IV|
Ordinal Multidimensional Scaling (MDS) has become a central approach for analyzing value structures in cross-cultural studies. Starting from regional hypotheses, MDS displays the discrimina-bility of value types in an easily accessible geometric represent-tation. Furthermore, this approach is relatively free from mathe-ma¬tical restrictions and additional assumptions not relevant to the problem under study (Borg & Shye, 1995). However, MDS configurations of identical data sets may differ, depending on the respective starting configuration. Such artefacts can be avoided by computing a weakly constrained confirmatory MDS. Drawing on Schwartz' (1992) value theory, the construction of a design matrix is proposed which specifies his model geometrically. This matrix serves as the basis for deriving a starting configuration that is tailored to the value instrument applied (Bilsky, Gollan & Döring, 2007). Its use is demonstrated by analyzing data sets collected with different instruments.