Work

Bayes factors functions based on test statistics and non-local moment prior densities

Year: 2024

Type: article

Abstract: We describe Bayes factors based on z , t , χ 2 , and F statistics when non-local moment prior distributions are used to define alternative hypotheses. The non-local alternative prior distributions are centered on standardized effects. The prior densities include a dispersion parameter that can be used to model prior precision and the variation of effect sizes across replicated experiments. We examine the convergence rates of Bayes factors under true null and true alternative hypotheses and show how these Bayes factors can be used to construct Bayes factor functions. Examples illustrate the application of resulting Bayes factors functions to psychological experiments.

Source: Statistics & Probability Letters

DOI: 10.1016/j.spl.2024.110330

Authors: Saptati Datta, Riana Guha, Rachael Shudde, Valen E. Johnson

Institution: Texas A&M University

Language: English

Topic: Statistical Methods and Bayesian Inference

Subfield: Statistics and Probability

Field: Mathematics

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $3,010

Funders: National Science Foundation, Division of Mathematical Sciences