Porovnat metody
Prohlédněte si vybrané metody vedle sebe; řádky, které se liší, jsou zvýrazněny.
| Analýza přerušených časových řad ve výzkumu vzdělávání× | Párování na základě skóre propensity× | |
|---|---|---|
| Obor≠ | Kauzální inference | Statistika ve výzkumu |
| Rodina≠ | Regression model | Process / pipeline |
| Rok vzniku≠ | 1979-2002 | 1983 |
| Tvůrce≠ | Shadish, Cook & Campbell (quasi-experimental design); Wagner et al. (segmented regression formalization) | Paul Rosenbaum and Donald Rubin |
| Typ≠ | Quasi-experimental causal inference | Method |
| Původní zdroj≠ | Shadish, W. R., Cook, T. D., & Campbell, D. T. (2002). Experimental and Quasi-Experimental Designs for Generalized Causal Inference. Houghton Mifflin. ISBN: 978-0395615560 | 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≠ | ITS in education, educational ITS, segmented regression in education, policy interrupted time series | PSM, propensity score weighting, covariate balance |
| Příbuzné≠ | 4 | 3 |
| Shrnutí≠ | Interrupted time series (ITS) analysis is a quasi-experimental design that estimates the causal effect of an education policy or intervention by examining whether an outcome trend changes abruptly at the point of implementation. Applied to education, it is used to evaluate reforms, curriculum changes, testing policies, and school interventions using routinely collected longitudinal data without a randomised control group. | 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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