Bayesian Hypothesis Testing Research
Bayesian hypothesis testing research is a quantitative design in which competing hypotheses are evaluated by updating prior beliefs with observed data to produce posterior probabilities and Bayes factors. Unlike frequentist null-hypothesis significance testing, it quantifies the relative evidence for each hypothesis, supports optional stopping, and allows accumulation of evidence across studies without inflating Type I error rates.
Source record
Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.
- Jeffreys, H. (1961). Theory of Probability (3rd ed.). Oxford University Press. · ISBN 978-0198503682
- Wagenmakers, E.-J. (2010). A practical solution to the pervasive problems of p values. Psychonomic Bulletin and Review, 14(5), 779–804. · URL
Curated claims
Claims persisted in the evidence ledger, each with its own assessment.
This view does not invent a claim assessment when the ledger has none.
Related methods
Generated from the method graph and shown as machine-suggested relations — no evidence claim is inferred.