A Comparison of Selected Empirical Methods for Assessing the Structure of Responses to Test Items

By R. Tate. 2003

149 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/9c1fb25715b29eb510fdc88bf0b72dc73c19daf0

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In Computer Networks and Communications

In Management Science and Operations Research

Citations in the corpus

Linking antisocial behavior, substance use, and personality: an integrative quantitative model of the adult externalizing spectrum. (2007, background): “The flexibility and accuracy of cluster analytic techniques have led to increasing recognition and recommendation of their use in the delineation of factor structure, especially in cases in which variables are highly correlated (Bacon, 2001; Tate, 2003; van Abswoude, Vermunt, Hemker, & van der Ark, ”
Item Parameter Estimation for the MIRT Model (2010, methodology): “However, Tate (2003) did focus on item parameter recovery, among other things, which allows for a direct comparison with the results of the current research.”
Factor Analysis with Ordinal Indicators: A Monte Carlo Study Comparing DWLS and ULS Estimation (2009, methodology): “Tate (2003) conducted a comparison of methods with dichotomous indicators with correlated and uncorrelated factors, and found that DWLS and ULS showed comparable parameter recovery across all conditions of number of factors, item difficulty, and factor loading.”
Assessing unidimensionality: A comparison of Rasch modeling, Parallel analysis, and TETRAD (2007, methodology): “More recently, Tate (2003) conducted a review of methods and indices employed with dichotomous items, finding that options for assessing dimensionality had expanded and improved, and that most methods perform effectively “within the limits of their associated perspectives and assumptions.””
Rethinking Internal Consistency in Cronbach's Alpha (2017, methodology): “The first step in establishing unidimensionality is to conduct a principal components analysis (PCA) of a set of items (Green & Thompson, 2005; Tate, 2003).”
Copula Functions for Residual Dependency (2007, methodology): “Various types of tools have been developed to detect local item or residual dependencies (see, e.g., Chen & Thissen, 1997; Holland & Rosenbaum, 1986; Rosenbaum, 1984; Yen, 1984; or, for a recent comparison, see Tate, 2003 ).”