Articles citing Bartos & Schimmack (2022). Estimating replication rates and discover rates. Meta-Psychology [PDF] in decreasing order of publication date.
2023
Schimmack U, Bartoš F (2023) Estimating the false discovery risk of (randomized) clinical trials in medical journals based on published p-values. PLoS ONE 18(8): e0290084. https://doi.org/10.1371/journal.pone.0290084
In this article, z-curve2.0 is used to estimate the false discovery risk (FDR) in clinical trials published in medical journals. The key finding is that the FDR with the conventional alpha level of .05 is 14% and can be reduced to less than 5% by using alpha of .01. There were few moderators by journal or time period, suggesting that research practices in clinical trials have not changed in response to concerns that most published results are false (Ioannidis, 2005). The reason may be that few medical researchers believed this claim. Low power may persist because medical research often relies on specific patient populations that are small. Z-curve also revealed publication bias in abstracts of clinicial trials, suggesting that preregistration does not fully eliminate outcome selection. Whether this bias also affects results reported in the actual article remains to be examined.
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