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。
| DINAモデル× | 必要条件分析× | |
|---|---|---|
| 分野 | 心理測定学 | 心理測定学 |
| 系統 | Latent structure | Latent structure |
| 提唱年≠ | 2001 | 2016 |
| 提唱者≠ | Brian Junker, Klaas Sijtsma | Jan Dul |
| 種類≠ | Discrete latent class model | Set-theoretic configurational analysis |
| 原典≠ | Junker, B. W., & Sijtsma, K. (2001). Cognitive assessment models with few assumptions, and connections with nonparametric item response theory. Applied Psychological Measurement, 25(3), 258-272. DOI ↗ | Dul, J. (2016). Necessary Condition Analysis (NCA): Logic and methodology of "necessary but not sufficient" causality. Organizational Research Methods, 19(1), 10-52. DOI ↗ |
| 別名 | DINA | NCA |
| 関連≠ | 4 | 5 |
| 概要≠ | The DINA Model (Deterministic Inputs, Noisy Outputs) is a cognitive diagnostic model developed by Junker and Sijtsma (2001) that classifies examinees into latent skill classes based on their item response patterns. DINA assumes a deterministic relationship between skill mastery and correct responses, with probabilistic error accounting for guessing and slips. | Necessary Condition Analysis (NCA) is a set-theoretic method developed by Dul (2016) that identifies conditions necessary (but not necessarily sufficient) for an outcome to occur. Unlike regression, which estimates average effects, NCA identifies absolute thresholds: conditions that must be present at a certain level for the outcome to be possible, regardless of other factors. |
| ScholarGateデータセット ↗ |
|
|