ssdBFs {BayesRepDesign}

R Documentation

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)

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