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The influential claim that most published results are false raised concernsabout the trustworthiness and integrity of science. Since then, there have beennumerous attempts to examine the rate of false-positive results that havefailed to settle this question empirically. Here we propose a new way toestimate the false positive risk and apply the method to the results of(randomized) clinical trials in top medical journals. Contrary to claims thatmost published results are false, we find that the traditional significancecriterion of $\alpha = .05$ produces a false positive risk of 13%. Adjusting$\alpha$ to .01 lowers the false positive risk to less than 5%. However, ourmethod does provide clear evidence of publication bias that leads to inflatedeffect size estimates. These results provide a solid empirical foundation forevaluations of the trustworthiness of medical research.

Estimating the false discovery risk of (randomized) clinical trials in medical journals based on published p-values