Sequential Analyses using Effect Size Confidence Intervals: A Simulation-Based Approach

Read the full article See related articles

Listed in

This article is not in any list yet, why not save it to one of your lists.
Log in to save this article

Abstract

Sequential Bayesian analyses have been suggested as a means for efficient hypothesis-testing within psychology, often substantially reducing the sample sizes required. In the context of clinical psychology, trial designs using sequential Bayesian analyses have been proposed as a way to accelerate psychological treatment development. However, a focus on Bayesian analyses as a means to conduct sequential testing may hinder uptake of such methods due to a lack of familiarity amongst many researchers. Demonstrating how equivalent sequential analyses are possible using non-Bayesian (e.g., frequentist) analyses could increase the accessibility of these methods and thus the extent to which psychological treatment development research can benefit from more time and resource-efficient trial designs. This paper demonstrates a simple method for sequential testing based on confidence intervals around effect size estimates, and illustrates comparative efficiency to an approach based on Bayes factors.

Article activity feed