| I've sat this out for long time, but I've got to say that it's hilarious watching the HN community—mostly made up of engineers—constantly harp about the replication crisis in Psychology. In some cases effect may be real even though the studies aren't replicating today. There are several factors. Replication in psychology isn't as easy as in the physical sciences. Let me use an example from another field to give you an idea. If I asked you to translate the sentence: "He took the train for London at eight am." into French, would you translate "London" as "London" or as "Paris?" In other words the social context—social norms, expectations, attitudes—from when many of these studies which don't replicate today has shifted, such that re-running the study verbatim might fail to...replicate. However say you do try to adapt the study to adjust for the shift in context, then you could also say that the replication isn't valid because you didn't re-run the study exactly as specified. People aren't robots, so we can just re-run the unit tests on them and expect the exact same results. People aren't even self contained robots, we are social beings, and are very strongly affected by our peers. We aren't swimming in the same water that we were swimming in when these studies were done. We need new studies for each of these effects that are designed with today's reality in mind. But. No matter how one tries to 'replicate' an old psychology result, it will leave room for skepticism. It just won't be able to account for the 'translation' required without leaving room for doubt. I guess the most important thing we could learn from this is that it's important to replicate any current studies right now, and not wait forty years to do so. |
It's not just bad (vacuous) science, at its core it's people who act in a bad (selfish, non-scientific) ways: https://statmodeling.stat.columbia.edu/2016/09/21/what-has-h...
> I guess the most important thing we could learn from this is that it's important to replicate any current studies right now, and not wait forty years to do so.
Yes, that too, but what's even more important is to shift into a mindset that starts with good models, good data generation processes (ie. experiments), then we can check and compare their predictive power. Otherwise we get these statistically flawless abominations that prove ESP:
https://statmodeling.stat.columbia.edu/2011/01/11/one_more_t...
And, sure, yeah, it's hard to do this. But otherwise we'll have nothing more than just-so stories supported by random data that happened to break through some significance threshold.