Statistics & Data Science · Causal Inference
A topic within Causal Inference, itself one of 10 topics in that field and part of Statistics & Data Science.
Assumes you know the vocabulary.
Principles of Confounder Selection
Tyler J. VanderWeele · 2019
Argues the common practice of adjusting for anything associated with the outcome is wrong, and gives a smaller graphical rule for which variables to…
Primary sources and full treatments.
The Effectiveness of Adjustment by Subclassification in Removing Bias in Observational Studies
William G. Cochran · 1968
Shows that sorting units into five subclasses on a confounder removes most of the bias adjusting for it in full would remove, giving a simple rule of…
+1 more at this level
3 works
Tyler J. VanderWeele
Argues the common practice of adjusting for anything associated with the outcome is wrong, and gives a smaller graphical rule for which variables to include that avoids inducing new bias by controlling for the wrong ones.
link checked 17 Sept 2026William G. Cochran
Shows that sorting units into five subclasses on a confounder removes most of the bias adjusting for it in full would remove, giving a simple rule of thumb still used to justify coarse stratification.
link checked 17 Sept 2026Sander Greenland, Judea Pearl & James M. Robins
Translates confounding, selection bias and adjustment into graphical criteria on a causal diagram, replacing case-by-case epidemiological judgement about which variables to control for with a procedure that can be checked.
link checked 17 Sept 2026