Porovnat metody
Prohlédněte si vybrané metody vedle sebe; řádky, které se liší, jsou zvýrazněny.
| Regresní diskontinuální design ve výzkumu vzdělávání× | Párování na základě skóre propensity× | |
|---|---|---|
| Obor≠ | Kauzální inference | Statistika ve výzkumu |
| Rodina≠ | Regression model | Process / pipeline |
| Rok vzniku≠ | 1960 (origination); 1999-2010 (education economics canon) | 1983 |
| Tvůrce≠ | Thistlethwaite & Campbell (1960); popularized in education economics by Angrist & Lavy (1999), Lee & Lemieux (2010) | Paul Rosenbaum and Donald Rubin |
| Typ≠ | Quasi-experimental causal inference | Method |
| Původní zdroj≠ | Lee, D. S., & Lemieux, T. (2010). Regression discontinuity designs in economics. Journal of Economic Literature, 48(2), 281-355. DOI ↗ | 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 ↗ |
| Další názvy≠ | RDD in education, education RD design, sharp RDD education, score-cutoff design | PSM, propensity score weighting, covariate balance |
| Příbuzné≠ | 5 | 3 |
| Shrnutí≠ | Regression discontinuity design (RDD) in education research exploits a score-based eligibility cutoff — such as a test score threshold, GPA requirement, or age cutoff — to estimate the causal effect of a program, intervention, or policy on student or school outcomes. Units just below and just above the cutoff are treated as near-randomly assigned, enabling credible causal inference without a randomized trial. | Propensity score matching (PSM) is a method for reducing confounding bias in observational studies by balancing baseline characteristics between treatment groups, simulating randomization. Developed by Rosenbaum and Rubin (1983), it estimates the probability of receiving treatment given observed covariates, then matches or weights treated and control individuals with similar treatment probabilities. Widely used in medicine, epidemiology, and policy evaluation when randomized trials are infeasible or unethical, enabling estimation of treatment effects while controlling for selection bias. |
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