Bayesian prediction intervals for assessing P-value variability in prospective replication studies.

ABSTRACT: Increased availability of data and accessibility of computational tools in recent years have created an unprecedented upsurge of scientific studies driven by statistical analysis. Limitations inherent to statistics impose constraints on the reliability of conclusions drawn from data, so misuse of statistical methods is a growing concern. Hypothesis and significance testing, and the accompanying P-values are being scrutinized as representing the most widely applied and abused practices. One line of critique is that P-values are inherently unfit to fulfill their ostensible role as measures of credibility for scientific hypotheses. It has also been suggested that while P-values may have their role as summary measures of effect, researchers underappreciate the degree of randomness in the P-val

SUBMITTER: Vsevolozhskaya O 

PROVIDER: S-EPMC5802740 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature