Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Mchanganuo wa Milia Iliyoingiliwa katika Utafiti wa Elimu× | Kielelezo cha Athari Zilizowekwa za Data ya Paneli× | |
|---|---|---|
| Nyanja≠ | Uhitimisho wa Kisababishi | Ekonometriki |
| Familia | Regression model | Regression model |
| Mwaka wa asili≠ | 1979-2002 | 2014 |
| Mwanzilishi≠ | Shadish, Cook & Campbell (quasi-experimental design); Wagner et al. (segmented regression formalization) | Hsiao (textbook treatment); within transformation of panel data |
| Aina≠ | Quasi-experimental causal inference | Panel data regression |
| Chanzo asilia≠ | Shadish, W. R., Cook, T. D., & Campbell, D. T. (2002). Experimental and Quasi-Experimental Designs for Generalized Causal Inference. Houghton Mifflin. ISBN: 978-0395615560 | Hsiao, C. (2014). Analysis of Panel Data (3rd ed.). Cambridge University Press. DOI ↗ |
| Majina mbadala | ITS in education, educational ITS, segmented regression in education, policy interrupted time series | fixed effects model, within estimator, panel fixed-effects regression, Panel Veri — Sabit Etkiler Modeli |
| Zinazohusiana≠ | 4 | 5 |
| Muhtasari≠ | 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. | The Panel Data Fixed Effects model estimates relationships from panel data (the same units observed over several time periods) while controlling for unit- and/or time-specific effects, supporting causal inference. It is developed as the within estimator in standard treatments such as Hsiao's Analysis of Panel Data (2014). |
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