Evaluation: Understanding Rubin's Model of Causality

Rubin Causality (named for Donald Rubin) states that any relationship demonstrated in an experiment (where the units of analysis are randomly assigned to experimental and control groups) is a valid causal relationship and that any relationship that cannot be demonstrated in an experiment is not causal. However, the main dilemma we face is that if we show that" X causes Y", it is often impossible to show that "non-X does not cause Y" since you cannot see both potential outcomes at the same time for the same case. For example, if you show that taking statin drugs lowers Mary's LDL or "bad" cholesterol levels, you no longer have Mary with high LDL levels for which to see what happens if she is not given statin drugs. Thus Rubin's Model of Causality requires that we have randomly assigned control and treatment groups (in other words that we use an experimental design) to assess causality.