In a recent analysis of thousands of randomized controlled trials (RCT) in eight journals a simple method was offered which might enable skeptical scientist identification of data fabrication. Editor of the Anaesthesia journal John B. Carlisle of Torbay Hospital, UK, looked at baseline differences of means in more than 5000 randomized controlled trials, mainly in the field of Anesthesiology, but also more than 500 published in JAMA and more than 900 published in the New England Journal of Medicine . His study went online earlier this week. Analyzed articles were published between 2000 and 2015. In brief, if randomization was successful, baseline differences should be small. Giving p-values for baseline differences (in order to indicate successful randomization) is actually discouraged since they are not really interpretable, but Carlisle calculated them anyway. If the null hypothesis is true, p-values have a uniform distribution. So p-values between 0 and 1 would be equally likely.