Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Modelo DINA× | Análisis de Condiciones Necesarias× | |
|---|---|---|
| Campo | Psicometría | Psicometría |
| Familia | Latent structure | Latent structure |
| Año de origen≠ | 2001 | 2016 |
| Autor original≠ | Brian Junker, Klaas Sijtsma | Jan Dul |
| Tipo≠ | Discrete latent class model | Set-theoretic configurational analysis |
| Fuente seminal≠ | 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 ↗ |
| Alias | DINA | NCA |
| Relacionados≠ | 4 | 5 |
| Resumen≠ | 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. |
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