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← Causal Inference 101

4 min read

Covariate balance and why it matters

How to read balance tables and standardized mean differences after matching or weighting.

Covariate balance means treated and control groups have similar distributions of confounders. Without balance, outcome differences may reflect pre-existing differences, not treatment.

Standardized mean difference (SMD) is a common metric: below 0.1 on key covariates is a typical rule of thumb after matching, though context matters.

Before and after

Always compare balance before and after adjustment. Matching or IPW that fails to move SMDs probably means propensity model misspecification, poor overlap, or wrong covariate set.

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CausalLens runs matching, DiD, causal forests, DoWhy refutation, and more — with balance tables, sensitivity checks, and PDF export.

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