Learning Path

Causal Inference Methods – DAGs, Propensity Scores, and Instrumental Variables

Causal Inference Fundamentals → Regression Adjustment for Confounding

15 Knowledge Nodes · 15 Learning Steps · v0 Active

This path guides epidemiology and biostatistics students from foundational causal concepts to advanced analytical methods for estimating causal effects from observational data. It covers directed acyclic graphs (DAGs), propensity score methods, marginal structural models, G-computation, instrumental variables, and sensitivity analysis, emphasizing when and how to apply each approach.

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15 nodes32 edges3 relationships

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Learning Route

15 learning steps · 4 phases. Click any step to inspect it and see it on the Knowledge Map.

Phase 1

Foundation

4 steps

Phase 2

Core Concepts

4 steps

Phase 3

Advanced Topics

4 steps

Phase 4

Specialization

3 steps