Linganisha mbinu

	Kipimo cha Plasebo katika Utafiti wa Elimu	Njia ya Vigezo vya Ala (IV) kwa Utafutaji wa Kifungo
Nyanja	Uhitimisho wa Kisababishi	Uchumi wa Afya
Familia	Regression model	Process / pipeline
Mwaka wa asili	1990s–2000s	1990s (modern applications)
Mwanzilishi	Widely adopted in applied econometrics and education research; codified by Imbens, Wooldridge, Lee, and Lemieux	Angrist & Pischke (applied econometrics); rooted in econometric theory
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.	Angrist, J. D., & Pischke, J. S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton: Princeton University Press.
Majina mbadala	placebo regression, falsification test, placebo check, fake-treatment test	IV, two-stage least squares, TSLS, causal estimation
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.	Instrumental variables (IV) is an econometric method to estimate causal effects when treatment or exposure is not randomly assigned and confounding is severe or unmeasured. IV relies on a third variable (instrument) that influences treatment but does not directly affect the outcome, allowing researchers to isolate the causal effect from the noise of confounding. Developed extensively in econometrics (Angrist & Pischke, 1990s–2000s), IV methods are increasingly used in health economics and health services research to leverage natural experiments and policy changes.