Peter Henderson

When can we learn from observational data? In 1965 Austin Bradford Hill created a set of criteria that are required for a confident claim that an observed link between an exposure and an outcome is causal. It’s designed for situations where we lack studies with a comparison group. I’m taking this from David Spiegelhalter’s The Art of Statistics. The criteria are divided into three groups.

Direct evidence:

• The size of the effect is so large that it cannot be explained by plausible confounding.
• There is appropriate temporal and/or spatial proximity, in that cause precedes effect and effect occurs after a plausible interval, and/or cause occurs at the same time as the effect.
• Dose response and reversibility: the effect increases as the exposure increases, and the evidence is even strong if the effect reduces upon reduction of the dose.

Mechanistic evidence:

• There is a plausible mechanism of action, which could be biological, chemical, or mechanical, with external evidence for a ‘causal chain’.

Parallel evidence:

• The effect fits with what is known already.
• The effect is found when the study is replicated.
• The effect is found in similar, but not identical, studies.