Tree versus geometric representation of tests and items
1990
Loading...
View/Download File
Persistent link to this item
Statistics
View StatisticsJournal Title
Journal ISSN
Volume Title
Title
Tree versus geometric representation of tests and items
Authors
Published Date
1990
Publisher
Type
Article
Abstract
Factor-analytic techniques and multidimensional
scaling models are the traditional ways of representing
the interrelations among tests and items. Both can be
classified as geometric approaches. This study attempted
to broaden the scope of models traditionally
used, and to apply an additive tree model (ADDTREE)
that belongs to the family of network models. Correlation
matrices were obtained from three studies and
were analyzed using two representation models:
Smallest Space Analysis (SSA), which is a multidimensional
scaling model, and ADDTREE. The results of
both analyses were compared for the two criteria of
goodness of fit and interpretability. To enable a comparison
with the more traditional factor-analytic approach,
the data were also subjected to principal components
analyses. ADDTREE fared better in both
comparisons. Moreover, ADDTREE lends itself readily
to an interpretation in terms of hierarchical cluster
structure, whereas it is difficult to interpret SSA’s dimensions.
ADDTREE’S close fit to the data and its coherence
of presentation make it a convenient means of
representing tests and items. Index terms: additive
trees, ADDTREE, factor analysis, hierarchical clustering,
multidimensional scaling, Smallest Space Analysis.
Keywords
Description
Related to
Replaces
License
Series/Report Number
Funding information
Isbn identifier
Doi identifier
Previously Published Citation
Beller, Michal. (1990). Tree versus geometric representation of tests and items. Applied Psychological Measurement, 14, 13-28. doi:10.1177/014662169001400102
Suggested citation
Beller, Michal. (1990). Tree versus geometric representation of tests and items. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/107734.
Content distributed via the University Digital Conservancy may be subject to additional license and use restrictions applied by the depositor. By using these files, users agree to the Terms of Use. Materials in the UDC may contain content that is disturbing and/or harmful. For more information, please see our statement on harmful content in digital repositories.