Compară metode
Examinează metodele selectate una lângă alta; rândurile care diferă sunt evidențiate.
| Propensity Score Matching in Education× | School Effectiveness Modeling× | |
|---|---|---|
| Domeniu | Education | Education |
| Familie≠ | Process / pipeline | Regression model |
| Anul apariției≠ | 1983 | 2000 |
| Autorul original≠ | Rosenbaum & Rubin (method); educational application widespread (Stuart and others) | School effectiveness research tradition (Edmonds; Rutter; Teddlie & Reynolds; multilevel methods of Aitkin & Longford) |
| Tip≠ | Observational causal inference by matching treated and untreated units on treatment probability | Multilevel modeling of school contributions to student outcomes net of intake |
| Sursa seminală≠ | Rosenbaum, P. R., & Rubin, D. B. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika, 70(1), 41–55. DOI ↗ | Teddlie, C., & Reynolds, D. (2000). The International Handbook of School Effectiveness Research. Falmer Press. ISBN: 9780750706070 |
| Denumiri alternative | Educational Propensity Score Matching, PSM in Education, Propensity Matching for School Effects, Observational Causal Matching | School Effects Research, Educational Effectiveness Modeling, School Performance Modeling, Differential School Effectiveness |
| Înrudite | 4 | 4 |
| Rezumat≠ | Propensity score matching estimates the causal effect of an educational treatment from observational data by pairing treated students, schools, or teachers with comparison units that had the same probability of receiving the treatment given their observed characteristics. Introduced by Rosenbaum and Rubin, it collapses many confounding variables into a single score and matches on it, approximating the balance a randomized experiment would create. In education — where randomizing program participation, retention, or school choice is often impossible — it is a widely used quasi-experimental tool. | School effectiveness modeling estimates how much, and in what ways, individual schools contribute to student outcomes once differences in what students bring with them are taken into account. Using multilevel (hierarchical) models, it adjusts for student intake — prior attainment, socioeconomic background — and isolates the residual variation attributable to schools. The field asks not just whether schools differ, but which factors make some schools more effective and for whom, distinguishing genuine school contributions from the composition of their intake. |
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