Sample Size and Power for Comparing Inequality Constrained Hypotheses
Determine the unconditional error probabilities for a set of simulated...
Determine the 'power' for a Bayesian hypothesis test
Determine the required sample size for a Bayesian hypothesis test
Compute a Bayes factor
Compute the complexity or fit for two hypotheses.
Evaluate a constraint matrix for a set of prior/posterior samples
Sample multiple datasets and compute the Bayes factor in each
Sample from prior or posterior distribution
A collection of methods to determine the required sample size for the evaluation of inequality constrained hypotheses by means of a Bayes factor. Alternatively, for a given sample size, the unconditional error probabilities or the expected conditional error probabilities can be determined. Additional material on the methods in this package is available in Klaassen, F., Hoijtink, H. & Gu, X. (2019) <doi:10.31219/osf.io/d5kf3>.