Fig. 1: Graphical representations for estimating causality in experimental and observational data. | Nature Computational Science

Fig. 1: Graphical representations for estimating causality in experimental and observational data.

From: Quantifying causality in data science with quasi-experiments

Fig. 1

a, Graphical representation of an experimental study, where there is no link between treatment X and confounder Z as X is randomized. b, Graphical representation of an observational study, where both colliders C and confounders Z can bias causal effect estimates.

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