Overview and Practice of Causal Inference in Observational Studies
نویسنده
چکیده
Therefore, if randomization is successful, a simple comparison among the observed potential outcomes is the causal effect. In other words, randomization helps simple two-sample test report causal inference results. In causal DAG, successful randomization means that there are no arrows from confounders to the exposure variable. This means that regardless of conditions of confounders, the exposure variable influences its related outcome marginally and unbiased. Thus randomization ensures both the potential outcome framework and casual DAG to attain unbiased causal effect [2].
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