Zaslavsky, "Bayesian hypothesis
testing in two-arm trials with dichotomous outcomes," Biometrics, vol.
He also addresses the role of hypothesis testing in the evaluation of theories, the relationship between hypothesis tests and confidence intervals, and the role of prior knowledge in Bayesian estimation and Bayesian hypothesis
The primary purpose is to investigate and to verify the need to evaluate statistical power and inferential error rates for Bayesian hypothesis tests.
The Bayes factor is a measure of the evidence from the current study and has a key role in Bayesian hypothesis testing.
Most applications of Bayesian hypothesis tests have been for exploratory research and have not specified a criterion for acceptable evidence.
lens--specifically, using Bayesian hypothesis testing as a model.
system imposes a constraint on top of the standard Bayesian hypothesis
Figure 4 Bayesian Hypothesis
Statements State A : [mu] = [[mu].sub.A] with Prior Probability = [P.sub.A] State B : [mu] = [[mu].sub.B] with Prior Probability = [P.sub.B] The cost of accepting state A when state B is true (cost (A|B)) is compared to the cost of accepting state B when state A is true (cost (B|A)).
Four appendixes include: (1) Panel Members Attending the Multiple Comparisons Meetings; (2) Introduction to Multiple Testing; (3) Weighting Options for Constructing Composite Domain Outcomes; and (4) The Bayesian Hypothesis
The author has organized the main body of his text into fourteen chapters covering specifying Bayesian models, the normal and studentAEs-t models, the Bayesian prior, assessing model quality, Bayesian hypothesis
testing and the Bayes factor, Bayesian decision theory, Monte Carlo and related iterative methods, and a variety of other related subjects.
The starting point for a Bayesian hypothesis test is the prior probability that the hypothesis of interest is true.
However, applying Bayesian analyses to simulated data indicates that these discrepancies can reflect low power and inferential errors in Bayesian hypothesis testing, particularly with diffuse prior probabilities (Kennedy, in press).