pors {BayesRepDesign}

Compute probability of replication success

Description

This function computes the probabiliy of replication success based on a success region for the replication effect estimate, a design prior, and a replication standard error. If the specified number of sites is larger than 1, the supplied success region has to be formulated in terms of the meta-analytic replication effect estimate across sites.

Usage

pors(sregion, dprior, sr, nsites = 1)

Arguments

sregion

Success region for replication effect estimate

dprior

Design prior object

sr

Standard error of replication effect estimate

nsites

Number of sites, defaults to 1. The sites are assumed to have the same standard error sr

Value

The probability of 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

dprior <- designPrior(to = 1.1, so = 1)
sregion <- successRegion(intervals = cbind(1.96, Inf))
pors(sregion = sregion, dprior = dprior, sr = 1)