Query ExplorerWeight MatrixPath Effect MatrixPathway Decomposerdo() vs obs() GapSensitivityPrior vs PosteriorAbductionMarkov Blanket
Why the weight matrix matters
The weight matrix is the skeleton of the structural causal model — the fitted linear coefficients that quantify how strongly each direct cause acts on each effect. Unlike correlation coefficients, these weights have a directional, mechanistic interpretation: holding all other parents fixed, a weight of +1.5 means one unit of cause produces 1.5 units of effect downstream, not merely that the two tend to move together.
The matrix makes model transparency concrete. Every quantitative claim — path effects, sensitivity scores, counterfactual predictions — is a composition of these weights across chains of edges. Inspecting the matrix is the first check that domain knowledge was correctly encoded and that the fitted model behaves as intended.
Start here
- 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