Study design in causal models

The causal assumptions, the study design and the data are the elements required for scientific inference in empirical research. The research is adequately communicated only if all of these elements and their relations are described precisely. Causal models with design describe the study design and the missing data mechanism together with the causal structure and allow the direct application of causal calculus and the concept of ignorability. The flow of the study is visualized by ordering the nodes of the causal diagram in two dimensions by their causal order and the time of the observation. Causal models with design offer a systematic and unifying view scientific inference and increase the clarity and speed of communication. Examples show graphical models for a salary survey, a clinical trial, a nested case-control study and a two-stage case-cohort study.