2023-02-03 Stat Cafe - Dr. Valen Johnson

• Time: Friday 02/03 from 1:00 PM to 2:00 PM
• Location: BLOC 503
• We will be ordering lunch boxes from Firehouse subs. If you are planning to attend the talk, please fill out the survey by Sunday night.
• Gallery

Topic

Bayes factor functions

Abstract

Bayes factors represent the ratio of probabilities assigned to data by competing scientific hypotheses. Drawbacks of Bayes factors are their dependence on prior specifications that define null and alternative hypotheses and difficulties encountered in their computation. To address these problems, we define Bayes factor functions (BFF) directly from common test statistics. BFFs depend on a single non-centrality parameter expressed as a function of standardized effect sizes. Plots of BFFs versus effect size provide informative summaries of hypothesis tests that can be easily aggregated across studies. Such summaries eliminate the need for arbitrary P-value thresholds to define ``statistical significance.’’ BFFs are available in closed form and can be computed easily from z, t, chi-squared, and F statistics.

The other authors include Sandipan Pramanik, Rachael Shudde, and Saptati Datta.