Goodness-of-Fit Assessment of Item Response Theory Models

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Why Ordinal Variables Can (Almost) Always Be Treated as Continuous Variables: Clarifying Assumptions of Robust Continuous and Ordinal Factor Analysis Estimation Methods (2020, methodology): “Hence, we think that the assessment of model fit should rely on bivariate distributions of observed variables (Maydeu-Olivares, 2013).”
A New Statistic for Evaluating Item Response Theory Models for Ordinal Data. CRESST Report 839. (2014, methodology): “Recent years have witnessed an increased interest in the formal evaluation of item response theory (IRT) models (Maydeu-Olivares, 2013).”
An Application of M2 Statistic to Evaluate the Fit of Cognitive Diagnostic Models (2016, background): “…Statistics 2016, Vol. 41, No. 1, pp. 3–26 DOI: 10.3102/1076998615621293 # 2015 AERA. http://jebs.aera.net stagnant due to the fact that the full-information statistics w2 and G2 are virtually useless in practice (e.g., Maydeu-Olivares, 2013) and other suitable alternatives remain underdeveloped.”
Handbook of Item Response Theory Modeling : Applications to Typical Performance Assessment (2014, unknown): “…(see, e.g., Wirth & Edwards, 2007), and for a long time, limited-information methods provided the only practically viable means for conducting formal model appraisal; although on that latter point, the situation has changed dramatically in the past few years (see, e.g., Maydeu-Olivares, 2013).”