porsSig: Probability of replication success based on significance

In BayesRepDesign: Bayesian Design of Replication Studies

Probability of replication success based on significance

Description

This function computes the probability to achieve replication success on statistical significance of the replication effect estimate.

Usage

porsSig(level, dprior, sr)

Arguments

level	Significance level for p-value of the replication 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. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.48550/arXiv.2211.02552")}

Examples

## specify design prior
to1 <- 2
so1 <- 1
dprior <- designPrior(to = to1, so = so1, tau = 0.1)
porsSig(level = 0.025, dprior = dprior, sr = c(0.5, 0.3))

BayesRepDesign documentation built on May 4, 2023, 1:07 a.m.