Doubly Robust Estimation in Education Research
Doubly robust estimation (DR) is a semiparametric causal inference approach that combines an outcome regression model with a propensity score model. In education research, it is used to estimate the causal effect of educational programs, interventions, or policies on student outcomes when treatment assignment is non-random but observed covariates can account for selection bias. The estimator is consistent if either — not necessarily both — of the two component models is correctly specified.
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- Bang, H., & Robins, J. M. (2005). Doubly Robust Estimation in Missing Data and Causal Inference Models. Biometrics, 61(4), 962-973. · DOI 10.1111/j.1541-0420.2005.00377.x
- Karim, M. E., Petkau, J., Gustafson, P., Tremlett, H., & BeAMS Study Group. (2018). Comparison of statistical approaches dealing with time-dependent confounding in drug effectiveness studies. Statistical Methods in Medical Research, 27(6), 1709-1722. · DOI 10.1177/0962280216668554
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