Is the treatment beneficial? Causal Inference with Ordinal Outcomes: A Bayesian Solution

Randomized experiments with ordinal outcomes are common across scientific applications, but conventional causal estimands such as the average treatment effect are difficult to interpret because ordinal categories lack meaningful numerical spacing. Two interpretable estimands, the probabilities that