Bayesian Estimation Improves Prediction of Outcomes After Epilepsy Surgery
We estimated the statistical power of studies predicting seizure freedom after epilepsy surgery. We extracted data from a Cochrane meta-analysis. The median power across all studies was 14%. Studies with a median sample size or less (n ≤ 56) and a statistically significant result exaggerated the true effect size by a factor of 5.4, while the Bayesian estimate of the odds ratio only exaggerated the true effect size by a factor of 1.6. We conclude that Bayesian estimation of odds ratios attenuates the exaggeration of significant effect sizes in underpowered studies. This result could improve interpretation of studies with small sample sizes.
Authors
- Robert T. Krafty (ORCID: https://orcid.org/0000-0003-1478-6430)
- Adam S. Dickey (ORCID: https://orcid.org/0000-0003-4710-1290)
- Nigel P. Pedersen (ORCID: https://orcid.org/0000-0002-8494-0635)
- AMMAR A. RASHIED
- Vineet Reddy
Institutions
- Emory University (US)
- Flinders University (AU)
- Baylor College of Medicine (US)
- UC Davis Health (US)
- University of California, Berkeley (US)
Publication Details
- Journal
- Annals of Clinical and Translational Neurology
- Published
- 2025-12-18
- DOI
- https://doi.org/10.1002/acn3.70284
- Primary Topic
- Epilepsy research and treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Citizens United for Research in Epilepsy
- National Institutes of Health
- National Institute of General Medical Sciences
- National Institute of Neurological Disorders and Stroke
- National Center for Advancing Translational Sciences