手法を比較

	部分評点モデル（PCM / GPCM）	因子分析（EFA）
分野	心理測定学	統計学
系統	Latent structure	Latent structure
提唱年	1982	—
提唱者	Geoff N. Masters (PCM, 1982); Eiji Muraki (GPCM, 1992)	—
種類	Item Response Theory / Polytomous IRT	Latent variable / dimension reduction
原典	Masters, G. N. (1982). A Rasch model for partial credit scoring. Psychometrika, 47(2), 149–174.	Fabrigar, L. R., Wegener, D. T., MacCallum, R. C. & Strahan, E. J. (1999). Evaluating the use of exploratory factor analysis in psychological research. Psychological Methods, 4(3), 272–299.
別名	Kısmi Kredi Modeli (PCM / GPCM), Generalized Partial Credit Model, GPCM, PCM	common factor analysis, açımlayıcı faktör analizi, factor analysis
関連	5	4
概要	The Partial Credit Model is an extension of the Rasch measurement framework designed for ordered polytomous items — items whose responses fall into more than two ordered categories, such as partial-credit tasks in performance assessment or open-ended scoring rubrics. Proposed by Geoff Masters in 1982 and later generalised by Eiji Muraki in 1992, the model estimates a separate threshold (step) parameter for each adjacent-category transition within every item, allowing fine-grained calibration of how much each additional credit level contributes to locating a person on the latent trait.	Exploratory factor analysis reduces a large set of observed variables into a smaller number of latent common factors. It is widely used in scale development and psychometrics to uncover the dimensional structure that underlies a set of correlated items, without specifying that structure in advance.