Objective: The role of classical and Bayesian statistical approaches remains in dispute in health services research and policy. The goal of this study was to determine if results differ when both analytic techniques are used with the same data set.
Design: We searched MEDLINE and related databases for English-language articles published January 1, 1978 through August 31, 1999. We combined Bayesian and classical statistics search terms and their variants with randomized control trials (RCTs) and meta-analyses.
Results: Searches found 18 studies in 14 publications that met all review criteria--nine RCTs, eight meta-analyses, and one epidemiologic estimate. Statistical analyses using both methods agreed in five RCTs, four meta-analyses, and for the epidemiologic estimates. For four RCTs where results disagreed, classical analysis found the experimental intervention was efficacious compared with the control, and Bayesian reanalysis concluded the intervention was not proven efficacious. Classical meta-analyses of the four studies where results disagreed concluded the experimental intervention was not better than the control; Bayesian reanalysis concluded it was efficacious.
Conclusion: Classical and Bayesian methods in this review exhibited important divergence of results. Disagreement on many fundamental beliefs between classical and Bayesian statistics means continuing debate. One way to resolve this debate is for proponents of each technique to decide together the circumstances for use of each method and analytic framework. If the experts do not agree on the methodologic requirements, other decision makers likely will force their own views.
Download full-text PDF |
Source |
|---|
Publication Analysis
Top Keywords
Similar Publications
The analysis of complex mechanisms within population data, and within sub-populations, can be empowered by combining datasets, for example to gain more understanding of change processes of health-related behaviours. Because of the complexity of this kind of research, it is valuable to provide more specific guidelines for such analyses than given in standard data science methodologies. Thereto, we propose a generic procedure for applied data science research in which the data from multiple studies are included.
View Article and Find Full Text PDFDeterminants of physical activity among female students based on the transtheoretical model.
Sci Rep
January 2025
Social Determinants of Health Research Center, Hamadan University of Medical Sciences, Hamadan, Iran.
This study investigates factors influencing physical activity based on the Transtheoretical model (TTM) among adolescents. This study was conducted on 745 individuals between the ages of 12 and 16 years and was analyzed using a generalized linear model (GLM) approach with appropriate link functions using both classical and Bayesian frameworks. The results show that in model 1, the probit link function is a more appropriate approach to determine the risk factors for physical activity.
View Article and Find Full Text PDFTranscutaneous Auricular Vagus Nerve Stimulation Does Not Accelerate Fear Extinction: A Randomized, Sham-Controlled Study.
Psychophysiology
January 2025
Research Group Health Psychology, KU Leuven, Leuven, Belgium.
Transcutaneous auricular vagus nerve stimulation (taVNS) has been tested as a strategy to facilitate fear extinction learning based on the hypothesis that taVNS increases central noradrenergic activity. Four studies out of six found taVNS to enhance extinction learning especially at the beginning of extinction. Facilitatory effects of taVNS were mainly observed in US expectancy, less in fear-potentiated startle (FPS), and not in the skin conductance response (SCR).
View Article and Find Full Text PDFMachine learning with knowledge constraints for design optimization of microring resonators as a quantum light source.
Sci Rep
January 2025
Departemant of Physics and Energy Engineering, Amirkabir University of Technology, Tehran, Iran.
With careful design and integration, microring resonators can serve as a promising foundation for developing compact and scalable sources of non-classical light for quantum information processing. However, the current design flow is hindered by computational challenges and a complex, high-dimensional parameter space with interdependent variables. In this work, we present a knowledge-integrated machine learning framework based on Bayesian Optimization for designing squeezed light sources using microring resonators.
View Article and Find Full Text PDFBioinformatics identification based on causal association inference using multi-omics reveals the underlying mechanism of Gui-Zhi-Shao-Yao-Zhi-Mu decoction in modulating rheumatoid arthritis.
Phytomedicine
December 2024
Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu 610072, China. Electronic address:
Object: Rheumatoid arthritis (RA) is a prevalent and currently incurable autoimmune disease. Existing conventional medical treatments are limited in their efficacy, prolonged disease may lead to bone destruction, joint deformity, and loss of related functions, which places a huge burden on RA patients and their families. For millennia, the use of traditional Chinese medicine (TCM), exemplified by the Gui-Zhi-Shao-Yao-Zhi-Mu decoction (GZSYZM), has been demonstrated to offer distinct therapeutic advantages in the management of RA.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!