手法を比較
選択した手法を並べて確認できます。異なる行はハイライト表示されます。
| 二因子モデル（一般因子と特定因子）× | 因子分析（EFA）× | |
|---|---|---|
| 分野≠ | 心理測定学 | 統計学 |
| 系統 | Latent structure | Latent structure |
| 提唱年≠ | 1937 | — |
| 提唱者≠ | Holzinger & Swineford (1937); modern revival by Reise (2012) | — |
| 種類≠ | Confirmatory latent variable model | Latent variable / dimension reduction |
| 原典≠ | Reise, S. P. (2012). The Rediscovery of Bifactor Measurement Models. Multivariate Behavioral Research, 47(5), 667–696. DOI ↗ | 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. DOI ↗ |
| 別名≠ | Bifaktör Modeli — Genel ve Spesifik Faktörler, hierarchical factor model, general-specific factor model, Schmid-Leiman model | common factor analysis, açımlayıcı faktör analizi, factor analysis |
| 関連≠ | 6 | 4 |
| 概要≠ | The bifactor measurement model specifies that every indicator loads simultaneously on a single general factor and on one of several specific (group) factors. Formally introduced by Holzinger and Swineford in 1937 and brought into mainstream psychometrics by Reise (2012), it is now the standard tool for evaluating whether a multidimensional scale can legitimately yield a single composite score. | 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. |
| ScholarGateデータセット ↗ |
|
|