ssdBFs {BayesRepDesign}

Sample size determination for replication success based on the sceptical Bayes factor

Description

This function computes the standard error required to achieve replication success with a certain probability and based on the sceptical Bayes factor. The sceptical Bayes factor is assumed to be oriented so that values below one indicate replication success.

Usage

ssdBFs(
  level,
  dprior,
  power,
  searchInt = c(.Machine$double.eps^0.5, 2),
  paradox = TRUE
)

Arguments

level

Threshold for the sceptical Bayes factor below which replication success is achieved

dprior

Design prior object

power

Desired probability of replication success

searchInt

Interval for numerical search over replication standard errors

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

Value

Returns an object of class "ssdRS". See ssd for details.

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

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. doi:10.1111/rssb.12491

Examples

## specify design prior
to1 <- 0.2
so1 <- 0.05
dprior <- designPrior(to = to1, so = so1, tau = 0.03)
ssdBFs(level = 1/10, dprior = dprior, power = 0.9)