55 citations · 66 across the 17 of their papers we have counts for
12 papers · 1 filter
Sample-Specific Root Causal Inference with Latent Variables
Eric V. Strobl, Thomas A. Lasko
Root causal analysis seeks to identify the set of initial perturbations that induce an unwanted outcome. In prior work, we defined sample-specific root causes of disease using exog…
Identifying Patient-Specific Root Causes of Disease
Eric V. Strobl, Thomas A. Lasko
Complex diseases are caused by a multitude of factors that may differ between patients. As a result, hypothesis tests comparing all patients to all healthy controls can detect many…
Identifying Patient-Specific Root Causes with the Heteroscedastic Noise Model
Eric V. Strobl, Thomas A. Lasko
Complex diseases are caused by a multitude of factors that may differ between patients even within the same diagnostic category. A few underlying root causes may nevertheless initi…
Generalizing Clinical Trials with Convex Hulls
Eric V. Strobl, Thomas A. Lasko
Randomized clinical trials eliminate confounding but impose strict exclusion criteria that limit recruitment to a subset of the population. Observational datasets are more inclusiv…
Synthesized Difference in Differences
Eric V. Strobl, Thomas A. Lasko
We consider estimating the conditional average treatment effect for everyone by eliminating confounding and selection bias. Unfortunately, randomized clinical trials (RCTs) elimina…
Automated Hyperparameter Selection for the PC Algorithm
Eric V. Strobl
The PC algorithm infers causal relations using conditional independence tests that require a pre-specified Type I level. PC is however unsupervised, so we cannot tune using…