porsBFs: Probability of replication success based on the sceptical Bayes factor

Description

This function computes the probability to achieve replication success based on the sceptical Bayes factor. The sceptical Bayes factor is assumed to be oriented so that values below one indicate replication success.

Usage

porsBFs(level, dprior, sr, paradox = TRUE)

Value

The probability to achieve replication success

Arguments

level: Threshold for the sceptical Bayes factor below which replication success is achieved
dprior: Design prior object
sr: Replication standard error
paradox: Should the probability of replication success be computed allowing for the replication paradox (replication success when the effect estimates from original and replication study have a different sign)? Defaults to TRUE

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")

Pawel, S. and Held, L. (2020). The sceptical Bayes factor for the assessement of replication success. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 84(3), 879-911. tools:::Rd_expr_doi("10.1111/rssb.12491")

Examples

Run this code

## specify design prior
to1 <- 0.2
so1 <- 0.05
dprior <- designPrior(to = to1, so = so1)
porsBFs(level = 1/3, dprior = dprior, sr = 0.05)

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