Causal reasoning implementing DAG construction, do-calculus, and intervention effect estimation
name causal-inference-engine description Causal reasoning implementing DAG construction, do-calculus, and intervention effect estimation allowed-tools ["Bash","Read","Write","Edit","Glob","Grep"] metadata {"specialization":"scientific-discovery","domain":"science","category":"hypothesis-reasoning","phase":6} Causal Inference Engine Purpose Provides causal reasoning capabilities implementing DAG construction, do-calculus, and intervention effect estimation. Capabilities Causal DAG construction and validation Backdoor/frontdoor criterion checking Average treatment effect estimation Instrumental variable analysis Mediation analysis Sensitivity analysis for unmeasured confounding Usage Guidelines DAG Construction : Build causal graphs from domain knowledge Identification : Check if effects are identifiable Estimation : Apply appropriate estimation methods Sensitivity : Assess robustness to unmeasured confounding Tools/Libraries DoWhy CausalNex pgmpy EconML