Before revision:  We extend our results to p-hacking when there is also publication bias , and also consider what types of distributions arise under the alternative hypothesis that researchers engage in p-hacking. We show that the power of statistical tests for detecting p-hacking is low even if p-hacking is quite prevalent .
After revision:  We extend our results to p-hacking based on distributions of t-statistics can be problematic and may not control size. Our proposed tests are shown to have good properties in Monte Carlo studies and are applied to two datasets of p-values .