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| Propensity Score Matching in Education× | Μοντελοποίηση Προστιθέμενης Αξίας× | |
|---|---|---|
| Πεδίο≠ | Education | Ψυχομετρία |
| Οικογένεια≠ | Process / pipeline | Latent structure |
| Έτος προέλευσης≠ | 1983 | 1998 |
| Δημιουργός≠ | Rosenbaum & Rubin (method); educational application widespread (Stuart and others) | William Sanders, Sandra Horn |
| Τύπος≠ | Observational causal inference by matching treated and untreated units on treatment probability | Longitudinal student achievement modeling |
| Θεμελιώδης πηγή≠ | 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 ↗ | Kane, T. J., Rockoff, J. E., & Staiger, D. O. (2008). What does certification tell us about teacher effectiveness? Evidence from New York City. Economics of Education Review, 27(6), 615-631. DOI ↗ |
| Εναλλακτικές ονομασίες≠ | Educational Propensity Score Matching, PSM in Education, Propensity Matching for School Effects, Observational Causal Matching | VAM |
| Συναφείς | 4 | 4 |
| Σύνοψη≠ | 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. | Value-Added Modeling (VAM) is a method for assessing the contribution of schools or teachers to student achievement growth, developed by Sanders and Horn (1998). VAM isolates the effect of a teacher or school by comparing student gains (value added) while controlling for prior achievement and student characteristics. |
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