How do you handle confounders in observational studies?

medium

Answer

$(X\;\mathrm{in}\;E[Y\; \mid \;T, \;X])$
$(2) Matching / propensity score matching — trims to overlap region.$
$(3) Inverse probability weighting — reweight sample so treated and control look similar.$
$(4) Doubly robust: regression + IPW (consistent if either is correct).$
$(5) Instrumental variables — bypass unobserved confounders.$
$Unmeasured confounders are the fatal weakness — that's why RCTs are the gold standard.$

Check yourself — multiple choice

Not needed
Regression / matching / IPW / doubly robust adjust for observed confounders; unmeasured confounders → IV or admit non-identifiability
Only IV
Random

Confounders: regression / matching / IPW / DR / IV; unmeasured → IV or RCT.

#causal-inference

215 interview questions in this topic.