Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Kipimo cha Plasebo katika Utafiti wa Elimu× | Ulinganishaji wa Alama ya Mwelekeo× | |
|---|---|---|
| Nyanja≠ | Uhitimisho wa Kisababishi | Takwimu za Utafiti |
| Familia≠ | Regression model | Process / pipeline |
| Mwaka wa asili≠ | 1990s–2000s | 1983 |
| Mwanzilishi≠ | Widely adopted in applied econometrics and education research; codified by Imbens, Wooldridge, Lee, and Lemieux | Paul Rosenbaum and Donald Rubin |
| Aina≠ | Falsification / robustness check | Method |
| Chanzo asilia≠ | Imbens, G. W., & Wooldridge, J. M. (2009). Recent Developments in the Econometrics of Program Evaluation. Journal of Economic Literature, 47(1), 5-86. 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 ↗ |
| Majina mbadala≠ | placebo regression, falsification test, placebo check, fake-treatment test | PSM, propensity score weighting, covariate balance |
| Zinazohusiana≠ | 4 | 3 |
| Muhtasari≠ | A placebo test is a falsification check used in quasi-experimental education research to validate a causal design. By applying the same estimator to a time period, group, or outcome where no real effect should exist, researchers verify that their identification strategy is not picking up spurious patterns. A statistically significant placebo estimate signals a flaw in the design, while a null result supports its credibility. | 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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