title: A Test by Any Other Name: P Values, Bayes Factors, and Statistical Inference.
abstract: Procedures used for statistical inference are receiving increased scrutiny as the scientific community studies the factors associated with insuring reproducible research. This note addresses recent negative attention directed at p values, the relationship of confidence intervals and tests, and the role of Bayesian inference and Bayes factors, with an eye toward better understanding these different strategies for statistical inference. We argue that researchers and data analysts too often resort to binary decisions (e.g., whether to reject or accept the null hypothesis) in settings where this may not be required.
authors.affiliation: a Department of Statistics , University of California , Irvine.
authors.forename: Hal S
authors.initials: HS
authors.lastname: Stern
mesh_terms: D001499:Bayes Theorem; D035841:Behavioral Research / Q000379:methods; D003627:Data Interpretation, Statistical; D015233:Models, Statistical
keywords: Bayesian inference; confidence intervals; effect size; significance testing