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Direct linkLu, Rui; Keller, Bryan Sean – AERA Online Paper Repository, 2019
When estimating an average treatment effect with observational data, it's possible to get an unbiased estimate of the causal effect if all confounding variables are observed and reliably measured. In education, confounding variables are often latent constructs. Covariate selection methods used in causal inference applications assume that all…
Descriptors: Factor Analysis, Predictor Variables, Monte Carlo Methods, Comparative Analysis
