Research map / Probabilistic and scientific modeling / Treatment effects
Using Embeddings for Causal Estimation of Peer Influence in Social Networks
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| use embedding adjustment instead of unadjusted regression | peer contagion estimation · Pokec district confounder, high confounding | estimated effect (truth 1): 7.40 -> 1.17 | Helped |
| use embedding adjustment instead of parametric SBM baseline | peer contagion estimation · Pokec district confounder, high confounding | estimated effect (truth 1): 5.28 -> 1.17 | Helped |
| use embedding adjustment instead of unadjusted regression | peer contagion estimation · Pokec age confounder, high confounding | estimated effect (truth 1): 4.90 -> 1.11 | Helped |
| use embedding adjustment when there is no confounding | peer contagion estimation · Pokec district confounder, zero confounding | estimated effect (truth 1): 0.99 -> 0.84 | Hurt |
| use embedding adjustment instead of unadjusted regression (truth 0) | peer contagion estimation · vaccination binary outcome, district | estimated effect (truth 1): 2.03 -> 0.09 | Helped |
| use embedding adjustment instead of unadjusted regression (truth 0) | peer contagion estimation · vaccination binary outcome, age | estimated effect (truth 1): 0.12 -> 0.11 | No clear effect |
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