方法证据记录
Bayesian Model Testing Research
Bayesian model testing research is a quantitative design in which competing theoretical models or hypotheses are evaluated by comparing their marginal likelihoods given observed data. The central tool is the Bayes factor — a ratio that quantifies how much more likely the data are under one model than under another. Unlike null-hypothesis significance testing, Bayesian model testing yields direct evidence for or against specific hypotheses, incorporates prior knowledge, and can support a null hypothesis rather than merely failing to reject it.
源记录
引文逐字复制自方法源记录。这些引文不代表任何层级的验证。
Bayesian Model Testing Research Design
分类方法记录 · process-pipeline / research-design
- Kass, R. E., & Raftery, A. E. (1995). Bayes factors. Journal of the American Statistical Association, 90(430), 773–795. · DOI 10.1080/01621459.1995.10476572
- Jeffreys, H. (1961). Theory of Probability (3rd ed.). Oxford University Press. · ISBN 978-0198503682
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