Assessing essential unidimensionality of real data

Abstract

The capability of DIMTEST in assessing essential unidimensionality of item responses to real tests was investigated. DIMTEST found that some test data fit an essentially unidimensional model and other data did not. Essentially unidimensional test data identified by DIMTEST then were combined to form two-dimensional test data. The power of Stout’s statistic T was examined for these two-dimensional data. DIMTEST results on real tests replicated findings from simulated tests-T discriminated well between essentially unidimensional and multidimensional tests. T was also highly sensitive to major traits and insensitive to relatively minor traits that influenced item responses. Index terms: DIMTEST, essential unidimensionality, essential independence, multidimensionality, unidimensionality.