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Partial Identification of the Average Treatment Effect with Stochastic Counterfactuals and Discordant Twins
Brian Knaeble, Braxton Osting, Placede Tshiaba
We develop a novel approach to partially identify causal estimands, such as the average treatment effect (ATE), from observational data. To better satisfy the stable unit treatment…
Observational Causality Testing
Brian Knaeble, Braxton Osting, Placede Tshiaba
In prior work we have introduced an asymptotic threshold of sufficient randomness for causal inference from observational data. In this paper we extend that prior work in three mai…
Quantifying Sufficient Randomness for Causal Inference
Brian Knaeble, Braxton Osting, Placede Tshiaba
Spurious association arises from covariance between propensity for the treatment and individual risk for the outcome. For sensitivity analysis with stochastic counterfactuals we in…