BayesRepDesign (version 0.42)

porsTOST: Probability of replication success based on TOST equivalence

Description

This function computes the probability to achieve replication success based on establishing the absence of a practically relevant effect size with the Two One-Sided Tests (TOST) procedure in the replication study.

Usage

porsTOST(level, dprior, margin, sr)

Value

The probability to achieve replication success

Arguments

level

Significance level for the TOST p-value

dprior

Design prior object

margin

The equivalence margin > 0 for the equivalence region around zero that defines a region of practically irrelevant effect sizes

sr

Replication standard error

Author

Samuel Pawel

References

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

Anderson, S. F. and Maxwell, S. E. (2016). There's more than one way to conduct a replication study: Beyond statistical significance. Psychological Methods, 21(1), 1-12. tools:::Rd_expr_doi("10.1037/met0000051")

Examples

## specify design prior
to1 <- 2
so1 <- 0.05
dprior <- designPrior(to = to1, so = so1, tau = 0.1)
porsTOST(level = 0.1, dprior = dprior, margin = 0.3, sr = c(0.05, 0.03))