Why most published research findings are false
There is increasing concern that most current published research fi ndings are false. The probability that a research claim is true may depend on study power and bias, the number of other studies on the same question, and, importantly, the ratio of true to no relationships among the relationships probed in each scientifi c fi eld. In this framework, a research fi nding is less likely to be true when the studies conducted in a fi eld are smaller; when effect sizes are smaller; when there is a greater number and lesser preselection of tested relationships; where there is greater fl exibility in designs, defi nitions, outcomes, and analytical modes; when there is greater fi nancial and other interest and prejudice; and when more teams are involved in a scientifi c fi eld in chase of statistical signifi cance. Simulations show that for most study designs and settings, it is more likely for a research claim to be false than true. Moreover, for many current scientifi c fi elds, claimed research fi ndings may often be simply accurate measures of the prevailing bias. In this essay, I discuss the implications of these problems for the conduct and interpretation of research.