The assumptions underlying statistical analysis are rarely fully met. Pragmatists face the challenge of knowing when evidence is strong enough to justify action, and that’s where sensitivity analysis helps by expressing the robustness of inferences relative to potential biases. For instance, sensitivity indices can quantify how much of the observed effect would need to be bias-driven to alter conclusions. We are building on these ideas by developing the methods and associated resources listed