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ロバスト差次的項目機能 (Robust DIF)×確認的因子分析(CFA)×
分野心理測定学心理測定学
系統Latent structureLatent structure
提唱年1990s–2000s1969
提唱者Building on DIF work by Cleary & Hilton (1968) and Mantel-Haenszel by Holland & Thayer (1988); robust extensions developed through 1990s–2000sKarl Gustav Jöreskog
種類Item bias / fairness analysisHypothesis-testing latent variable model
原典Magis, D., Beland, S., Tuerlinckx, F., & De Boeck, P. (2011). A general framework and an R package for the detection of dichotomous differential item functioning. Behavior Research Methods, 43(3), 847–862. DOI ↗Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202. DOI ↗
別名Robust DIF, outlier-resistant DIF detection, robust item bias analysis, DIF with robust estimationCFA, confirmatory FA, measurement model, restricted factor analysis
関連64
概要Robust differential item functioning analysis detects items that behave differently across demographic groups after matching respondents on the underlying trait, while protecting the procedure against distortion by outliers, model misfit, or contaminated anchor items. It is applied in educational testing, clinical assessment, and survey research to ensure that a scale measures the same construct equally fairly for all groups.Confirmatory factor analysis tests a researcher-specified factor structure against observed data. Unlike exploratory approaches, the researcher decides in advance which indicators load on which latent factor, and the model is evaluated by how closely the implied covariance matrix reproduces the sample covariance matrix. CFA is central to scale validation, construct validity assessment, and measurement invariance testing.
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ScholarGate手法を比較: Robust Differential Item Functioning · Confirmatory factor analysis. 2026-06-17に以下より取得 https://scholargate.app/ja/compare