porsMeta {BayesRepDesign}

Probability of replication success based on meta-analytic significance

Description

This function computes the probability to achieve replication success on statistical significance of the fixed-effects meta-analytic effect estimate obtained from combining original and replication effect estimates.

Usage

porsMeta(level, dprior, sr)

Arguments

level

Significance level for p-value of the meta-analytic effect estimate (one-sided and in the same direction as the original effect estimate)

dprior

Design prior object

sr

Replication standard error

Value

The probability to achieve replication success

Author(s)

Samuel Pawel

References

Pawel, S., Consonni, G., and Held, L. (2022). Bayesian approaches to designing replication studies. arXiv preprint. doi:10.48550/arXiv.2211.02552

Examples

## specify design prior
to1 <- 2
so1 <- 1
dprior <- designPrior(to = to1, so = so1, tau = 0.1)
porsMeta(level = 0.025^2, dprior = dprior, sr = c(0.2, 0.1))