Bradford Hill Criteria for Causal Inference - King, Julian (2015)
We think we’re good at determining causality, but we suck at it One of the great challenges in evaluation is determining whether the results we’re seeing are because of the program we’re evaluating, some other influences out there in the big world, or random chance. At one level, this is an everyday, common sense task. As a species we’ve been makin g judgments about causation for a million years or so. Unfortunately, though, the way we are wired does not predispose us to logical thinkin g. We are inclined to be led astray by all sorts of biases and heurist ics. Over time, the rocket science for dealing with causation has beco me more sophisticated – a key example being the experimental study des ign or randomised controlled trial (RCT). And our evidence base about what works has been enriched as a result. But deep down we’re still bi ased, heuristical beings and not very good at thinking things through. We’ve become so enthusiastic about experimental designs we’re a littl e inclined to think they are the only way to determine whether A cause s B. Such a rigid view is no much use in the real world, where there a re all sorts of ethical, conceptual, practical and economic barriers t hat mean we can’t always conduct RCTs. Even where technically possible , they are not necessarily the best tool for every job.