False Positives, FWER, and FDR Explained

If you torture your data long enough, they will tell you whatever you want to hear - Mills (1993) False positives via statistical hypothesis testing are a severe problem in the scientific literature (Ioannidis, 2005). If a statistically significant finding looks real, but it’s not, and we make policy or clinical decisions based on this finding, it can have catastrophic consequences. Unfortunately, many researchers are still unaware exactly why false positives are so prevalent in the scientific literature, so, I’ve decided to explain some of the common reasons for the high prevalence. Read More