P in the right place: Revisiting the evidential value of P-values.

P-values are often calculated when testing hypotheses in quantitative settings, and low P-values are typically used as evidential measures to support research findings in published medical research. This article reviews old and new arguments questioning the evidential value of P-values. Critiques of the P-value include that it is confounded, fickle, and overestimates the evidence against the null. P-values may turn out falsely low in studies due to random or systematic errors. Even correctly low P-values do not logically provide support to any hypothesis. Recent studies show low replication rates of significant findings, questioning the dependability of published low P-values. P-values are poor indicators in support of scientific propositions. P-values must be inferred by a thorough understanding of the study's question, design, and conduct. Null hypothesis significance testing will likely remain an important method in quantitative analysis but may be complemented with other statistical techniques that more straightforwardly address the size and precision of an effect or the plausibility that a hypothesis is true.