Analyze Causal Inference

Estimate a causal effect with an explicit estimand, identification assumptions, design, diagnostics, and sensitivity. Use when the user asks whether a change caused an outcome, for difference-in-differences, IV, or target-trial emulation. Do not use to register a product experiment, forecast an unresolved future event, or critique a present explanation.

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Analyze Causal Inference

Name the estimand before choosing an estimator. If identification fails, say not identified instead of reporting a number. A narrow interval around a biased estimate is not strong causal evidence.

Open causal inference methods when choosing an adjustment set, design, or sensitivity method.

Use design-product-experiment when assignment can still be designed. Use forecast-with-calibration for a future event. Use analyze-system-dynamics when the question is mechanism over time rather than one contrast.

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