powerprior: Posterior Analysis for empirical Bayes powerprior

In wiesenfa/ESS: Quantification of prior informativeness in terms of prior effective and effective current sample size

Description

Calculates the posterior distribution for data data given a prior priormix, where the prior is a empirical Bayes power prior (Gravestock&Held, 2017). Does the same as postmix.powerprior. Maybe deprecated in the future.

Usage

## S3 method for class 'betaMix'
powerprior(prior, n, r, p.prior.a, p.prior.b, ...)
## S3 method for class 'normMix'
powerprior(prior, n, m, sigma, ...)

Arguments

prior	An RBesT mixture object with a single mixture component
n	sample size
r	Number of successes
m	Sample mean
sigma	Sample standard deviation
p.prior.a	in case of binary outcome, shape1 parameter of initial beta prior for successes.
p.prior.b	in case of binary outcome, shape2 parameter of initial beta prior for successes.
...

Author(s)

Manuel Wiesenfarth

References

Gravestock, I. and Held, L. (2017). Adaptive power priors with empirical bayes for clinical trials. Pharmaceutical statistics, 16(5):349-360.

See Also

package StudyPrior, postmix.powerprior

wiesenfa/ESS documentation built on June 19, 2019, 4:19 p.m.