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Autor/inNandakumar, Ratna
InstitutionIllinois Univ., Urbana. Dept. of Statistics.
TitelAssessing Dimensionality of a Set of Items--Comparison of Different Approaches.
Quelle(1992), (42 Seiten)
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Spracheenglisch
Dokumenttypgedruckt; online; Monographie
SchlagwörterAbility; Comparative Testing; Correlation; Equations (Mathematics); Estimation (Mathematics); Factor Analysis; Item Response Theory; Mathematical Models; Power (Statistics); Simulation; Test Construction; Test Items
AbstractThe performance of the following four methodologies for assessing unidimensionality was examined: (1) DIMTEST; (2) the approach of P. W. Holland and P. R. Rosenbaum; (3) linear factor analysis; and (4) non-linear factor analysis. Each method is examined and compared with other methods using simulated data sets and real data sets. Seven data sets, all with 2,000 examinees, were generated with 3 unidimensional and 4 2-dimensional data sets. Two levels of correlation between abilities were considered: p=0.3 and p=0.7. Eight real data sets were used; four were expected to be unidimensional, and the other four were expected to be two-dimensional. Findings suggest that, while the linear factor analysis often overestimated the number of underlying dimensions, the other three methods correctly confirmed unidimensionality, but differed in their ability to detect the lack of unidimensionality. DIMTEST showed excellent power in detecting the lack of unidimensionality. Holland and Rosenbaum's approach and non-linear factor analysis approaches showed good power, provided the correlation between abilities was low. Four tables present study data, and there is a 46-item list of references. (Author/SLD)
Erfasst vonERIC (Education Resources Information Center), Washington, DC
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