RoA: visual analytics support for deconfounded causal inference in observational studies

Abstract

The gold standard in medical research to estimate the causal effect of a treatment is the Randomized Controlled Trial (RCT), but in many cases these are not feasible due to ethical, financial or practical issues. Observational studies are an alternative, but can easily lead to doubtful results, because of unbalanced selection bias and confounding. Moreover, RCTs often only apply to a specific subgroup and cannot readily be extrapolated. In response, we present Rod of Asclepius (RoA), a novel visual analytics method that integrates modern techniques designed for identification of causal effects and effect size estimation with subgroup analysis. The result is an interactive display designed to combine exploratory analysis with a robust set of techniques, including causal do-calculus, propensity score weighting, and effect estimation. It enables analysts to conduct observational studies in an exploratory, yet robust way. This is demonstrated by means of a use case involving patients undergoing surgery, for which we collaborated closely with clinical researchers.