A Basis for Multidimensional Item Response Theory

By R. Mcdonald. 2000

145 citations recorded by the source corpus.

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

View Paper: https://www.semanticscholar.org/paper/fce786eea9190fa5f1a89be9c063333e61b56ed6

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

1. S. Reise
2. Mark G. Haviland
3. Tyler M. Moore
4. R. Hays
5. Julien Morizot
6. Noah D. Goodman
7. Mike Wu
8. Jia He

In Management Science and Operations Research

1. Mark G. Haviland
2. S. Reise
3. Tyler M. Moore
4. Julien Morizot
5. R. Hays
6. Noah D. Goodman
7. Mike Wu
8. Jia He

Citations in the corpus

• Bifactor Models and Rotations: Exploring the Extent to which Multidimensional Data Yield Univocal Scale Scores (2010, background): “If a structure has an IC basis (and that basis is more than just mere doublets), for example, we can justify substantively interpreting the factors, and items that cross-load on multiple factors can be viewed as blends of two or more dimensions (McDonald, 1999, 2000).”
• Measurement Equivalence of the Job Descriptive Index Across Chinese and American Workers: Results from Confirmatory Factor Analysis and Item Response Theory (2005, methodology): “Although some multidimensional IRT software packages have been developed, such as NOHARM (McDonald, 1997) and TESTFACT (Wilson, Wood, & Gibbons, 1991), many theoretical and practical issues remain unsettled (McDonald, 2000; Raju et al., 2002; Reckase, 1997).”
• Variational Item Response Theory: Fast, Accurate, and Expressive (2020, background): “For cases where multiple facets of ability contribute to performance, we consider multidimensional item response theory [1, 36, 29].”
• The role of the bifactor model in resolving dimensionality issues in health outcomes measures (2007, methodology): “Further comments on dimensionality and the bifactor model In discussing dimensionality issues McDonald [11, 12] makes strong use of the concept of independent-clusters (IC) latent structure.”
• On Detecting Systematic Measurement Error in Cross-Cultural Research: A Review and Critical Reflection on Equivalence and Invariance Tests (2018, background): “Various extensions have been developed and refined to accommodate multidimensional constructs and more cultural groups (e.g., Hartig & Höhler, 2008; McDonald, 2000).”