Porovnať metódy
Prezrite si vybrané metódy vedľa seba; riadky, ktoré sa líšia, sú zvýraznené.
| Váhovanie na základe skóre sklonu vo výskume vzdelávania× | Zodpovedajúce skóre sklonu× | |
|---|---|---|
| Odbor≠ | Kauzálna inferencia | Štatistika vo výskume |
| Rodina≠ | Regression model | Process / pipeline |
| Rok vzniku≠ | 1983 (theory); widely adopted in education research from 2000s | 1983 |
| Tvorca≠ | Rosenbaum & Rubin (foundational theory, 1983); Thoemmes & Kim (education-focused review, 2011) | Paul Rosenbaum and Donald Rubin |
| Typ≠ | Quasi-experimental causal inference | Method |
| Pôvodný zdroj≠ | 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 ↗ | 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 ↗ |
| Ďalšie názvy≠ | PSW in education, inverse probability weighting in education, IPW education, propensity weighting education | PSM, propensity score weighting, covariate balance |
| Príbuzné≠ | 5 | 3 |
| Zhrnutie≠ | Propensity score weighting (PSW) is a quasi-experimental technique that reweights observational samples so that treated and comparison students look similar on measured background characteristics, allowing credible causal estimates of educational interventions — such as program participation, instructional method, or school type — without random assignment. | 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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