| https://nulib.github.io/moderndive_book/7-causality.html https://bolt.mph.ufl.edu/6050-6052/unit-2/causation-and-expe... https://towardsdatascience.com/establishing-causality-part-1... https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6235704/ https://escholarship.org/uc/item/42v4w8k1 http://ippsr.msu.edu/public-policy/michigan-wonk-blog/random... https://www.cs.cornell.edu/courses/cs1380/2018sp/textbook/ch... I’ll leave open the possibility that it’s everyone else that’s wrong but RCTs are used to establish causality and are as much “proof” as you’re gonna get in science. Hell ya know what I’ll just let the actual paper explain it. > The second, more important advantage of randomized field experiments is that they can distinguish causation from correlation. The ability to prove causal relationships derives from the combination of two characteristics. The first is having a control group, that is, a group unaffected by the intervention (in our case, publication of a Wikipedia article on the topic) that can be used as a counterfactual to estimate the size of causal effects. The second is randomization, that is, random assignment into the control and intervention groups. With sufficient data and a sound experimental design, the experiment can reduce the probability of being misled by correlation or noise to whatever arbitrarily small value is desired. |
No, they're not. The real "gold standard" in science--the standard that prevails in, for example, physics or chemistry--is a controlled experiment. Not just a "randomized controlled trial", but a controlled experiment, where you can actually dictate exactly what state the things you are going to experiment on start out in. And the eventual output of controlled experiments is a predictive model--a model that can predict, accurately, what will happen if you run further experiments. That is what it takes to truly "establish causality".
But in most other domains, including the one under study here, controlled experiments simply cannot be done and predictive models with any kind of accuracy simply don't exist. The correct response to that unfortunate fact is to realize that we can never achieve the same level of confidence in these other domains as we can in domains like physics or chemistry where we can do controlled experiments. Unfortunately, the response "science" has settled on instead is to pretend that it doesn't matter--that because we can't do controlled experiments in these other domains, the universe will somehow magically lower its standards of what it takes to achieve the level of confidence we want. But the universe doesn't care what we can or can't achieve.