Constrained and confirmatory multidimensional
scaling (MDS) are not equivalent. Constraints refer to
the translation of either theoretical or data analytical
objectives into computational specifications. Confirmation
refers to a study of the balance between systematic
and random variation in the data for modeling of
the systematic part. Among the topics discussed from
this perspective are the role of substantive theory in
MDS studies, the type of constraints currently envisaged,
and the relationships with other data analysis
methods. This paper points out the possibility of using
either sampling models or resampling schemes to
study the stability of MDS solutions. Parallel to
Akaike’s (1974) information criterion for choosing one
out of many models for the same data, a general stability
criterion is proposed and illustrated, based on
the ratio of within to total spread of configurations issued
Heiser, Willem J & Meulman, Jacqueline. (1983). Constrained multidimensional scaling, including confirmation. Applied Psychological Measurement, 7, 381-404. doi:10.1177/014662168300700402
Heiser, Willem J.; Meulman, Jacqueline.
Constrained multidimensional scaling, including confirmation.
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