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And also increase public trust in what is published (less of the "first they said ... was bad for you, now they say ... is good for you", etc)
by calvano915 8y ago
And also increase public trust in what is published (less of the "first they said ... was bad for you, now they say ... is good for you", etc)
- nonbel 8y agoWell, the way research is usually run they look for "statistical significance" and try to have "power" of ~80% to find it.[1] The power is controlled by the sample size, which is a big determinant of how much is spent on the study so it is chosen to be the lowest acceptable value. Anyway, my point is if there is an 80% chance of getting a result and you run two trials with those same odds, then only about 64% of the studies will replicate with the correct result (in R): p = 0.8 res = t(replicate(1e5, sample(0:1, 2, prob = c(1 - p, p), replace = T))) # 0 = Replicated wrong result # 1 = Non-replicated result # 2 = Replicated correct result > table(rowSums(res)) 0 1 2 3944 32135 63921 So, the standard practice is designed to generate a large percentage of conflicting results. [1] 80% is the target, but is probably usually optimistic