Bayes factor design analysis: Planning for compelling evidence
Ludwig-Maximilians-Universität München · University of Amsterdam
Abstract
A sizeable literature exists on the use of frequentist power analysis in the null-hypothesis significance testing (NHST) paradigm to facilitate the design of informative experiments. In contrast, there is almost no literature that discusses the design of experiments when Bayes factors (BFs) are used as a measure of evidence. Here we explore Bayes Factor Design Analysis (BFDA) as a useful tool to design studies for maximum efficiency and informativeness. We elaborate on three possible BF designs, (a) a fixed-n design, (b) an open-ended Sequential Bayes Factor (SBF) design, where researchers can test after each participant and can stop data collection whenever there is strong evidence for either $\mathcal…
Citation impact
- FWCI
- 52.96
- Percentile
- 100%
- References
- 86
Authors
2Topics & keywords
- Frequentist inference
- Bayes factor
- Sample size determination
- Bayes' theorem
- Null hypothesis
- Bayesian probability
- Statistical power
- Contrast (vision)
- Sustainable cities and communities