Why total path effects matter
Direct weights measure one-step relationships. But causes rarely act through a single edge — they propagate through chains of mediators, each multiplying or attenuating the signal. The path effect matrix computes the total causal effect of each node on every other, summing contributions across all directed paths.
This is what a do() query delivers at the population level: the expected change in Y per unit change in do(X), accounting for all intermediate steps. Comparing this matrix to the weight matrix shows where indirect mechanisms dominate the direct connection — the places where an intervention's consequences arrive through routes the decision-maker may not have anticipated.
- Open the recommended scenario for this case
- Adjust observed evidence or intervention settings
- Move to a second tool without losing context
- Compare obs() versus do() where available
- Inspect paths, blankets, or CPT structure to explain the shift