Bayesian updating: increasing sample size during the course of a study.

ABSTRACT:

Background

A priori sample size calculation requires an a priori estimate of the size of the effect. An incorrect estimate may result in a sample size that is too low to detect effects or that is unnecessarily high. An alternative to a priori sample size calculation is Bayesian updating, a procedure that allows increasing sample size during the course of a study until sufficient support for a hypothesis is achieved. This procedure does not require and a priori estimate of the effect size. This paper introduces Bayesian updating to researchers in the biomedical field and presents a simulation study that gives insight in sample sizes that may be expected for two-group comparisons.

Methods

Bayesian updating uses the Bayes factor, which quantifies the degree of support for a hyp

SUBMITTER: Moerbeek M 

PROVIDER: S-EPMC8258966 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature