Testing Biased Randomization Assumptions and Quantifying Imperfect Matching and Residual Confounding in Matched Observational Studies

Kan Chen, Siyu Heng, Qi Long & Bo Zhang
One central goal of design of observational studies is to embed nonexperimental data into an approximate randomized controlled trial using statistical matching. Despite empirical researchers’ best intention and effort to create high-quality matched samples, residual imbalance due to observed covariates not being well matched often persists. Although statistical tests have been developed to test the randomization assumption and its implications, few provide a means to quantify the level of residual confounding due to observed covariates...
1 citation reported since publication in 2022.
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