Full-Information Item Bifactor Analysis of Graded Response Data

By Robert D. Gibbons, R. D. Bock, Donald Hedeker, David J. Weiss, E. Segawa, D. Bhaumik, David J. Kupfer, E. Frank, Victoria J. Grochocinski, Angela Stover. 2007

301 citations recorded by the source corpus.

Subfields: Food Science, Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/dafdb8f989cabb91062b5fade732ca477a483c4a

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Citations in the corpus

Metropolis-Hastings Robbins-Monro Algorithm for Confirmatory Item Factor Analysis (2010, background): “The hypothesized factor pattern superficially resembles the bifactor structure (e.g., Gibbons & Hedeker, 1992; Gibbons et al., 2007).”
The higher-order model imposes a proportionality constraint: That is why the bifactor model tends to fit better (2016, background): “…bifactor model appears to have become embraced in the area of psychometrics and personality in recent years (Chen, Hayes, Carver, Laurenceau, & Zhang, 2012; Gibbons et al., 2007; Gruhl, Erosheva, & Crane, 2013; Morin, Arens, & Marsh, in press; Reise, 2012; Rodriguez, Reise, &Haviland, in press).”
A GENERAL PROGRAM FOR ITEM‐RESPONSE ANALYSIS THAT EMPLOYS THE STABILIZED NEWTON–RAPHSON ALGORITHM (2013, background): “Special attention will be given to hierarchical structures such as bifactor models (Gibbons et al., 2007; Gibbons & Hedeker, 1982).”
The role of the bifactor model in resolving dimensionality issues in health outcomes measures (2007, methodology): “In theory, a computerized adaptive testing system based on the bifactor model could be developed [55].”
mirt: A Multidimensional Item Response Theory Package for the R Environment (2012, methodology): “…mirt package are the ﬁxed quadrature EM method for exploratory (Bock et al. 1988; Muraki and Carlson 1995) and bifactor (Gibbons and Hedeker 1992; Gibbons et al. 2007) models, and the Metropolis-Hastings Robbins-Monro method for exploratory (Cai 2010a) and conﬁrmatory (Cai 2010b) polytomous…”
Modeling Differential Item Functioning Using a Generalization of the Multiple-Group Bifactor Model (2013, methodology): “The model has been extended to item-level analysis for binary data by Gibbons and Hedeker (1992) and for polytomous data by Gibbons et al. (2007).”
Item Banks for Measuring Emotional Distress From the Patient-Reported Outcomes Measurement Information System (PROMIS®): Depression, Anxiety, and Anger (2011, background): “Some (Gibbons et al., 2007; Gibbons & Hedeker, 1992; Reise, Morizot, & Hays, 2007) have argued that a bifactor model may be warranted in such circumstances (although the bifactor model assumes that its group factors are uncorrelated).”