DAGs
Everything on Aqrab tagged DAGs — grouped into one landing page so readers can go deeper by problem family instead of bouncing around the archive blind.
Overadjustment Bias: When More Covariates Make Causal Inference Worse
A practical guide to overadjustment bias for clinical researchers. Covers mediators, colliders, post-treatment variables, propensity score misuse, and why the biggest adjustment set is often the least credible one.
Front-Door Criterion: The Causal Backdoor Alternative Nobody Uses Enough
A practical guide to the front-door criterion for causal inference. Covers full mediation, mediator-outcome confounding, identification logic, DAG requirements, and why most real datasets are nowhere near clean enough for a credible front-door design.
DAG Construction: How to Draw a Causal Graph Before You Touch the Model
A practical guide to DAG construction for clinical researchers. Covers time ordering, node selection, confounders vs mediators vs colliders, minimally sufficient adjustment sets, and why most covariate lists are just causal confusion wearing a regression badge.
Structural Causal Models & DAGs: A Practical Guide for Clinical Researchers
The causal framework behind every method you use. Covers DAGs, d-separation, do-calculus, backdoor/frontdoor criteria, mediation analysis, and how to draw the graph that makes your analysis work.
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