When you're operating in an underpowered environment, you have two problems. One is the obvious that you have a very high chance of false negative. And it could be that the smaller the power that you are operating with, if you do detect something, even if it is real, the magnitude of the effect size will be substantially inflated.
John Ioannidis of Stanford University talks with EconTalk host Russ Roberts about his research on the reliability of published research findings. They discuss Ioannidis's recent study on bias in economics research, meta-analysis, the challenge of small sample analysis, and the reliability of statistical significance as a measure of success in empirical research.