BayesRepDesign (version 0.42)

ssdPs: Sample size determination for replication success based on the sceptical p-value

Description

This function computes the standard error required to achieve replication success with a certain probability and based on the sceptical p-value.

Usage

ssdPs(level, dprior, power)

Value

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

Arguments

level

Threshold for the (one-sided) sceptical p-value below which replication success is achieved

dprior

Design prior object

power

Desired probability of replication success

Author

Samuel Pawel

Details

The sceptical p-value is assumed to be uncalibrated as in Held (2020). The package ReplicationSuccess allows for sample size and power calculations with the recalibrated sceptical p-value (https://CRAN.R-project.org/package=ReplicationSuccess).

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")

Held, L. (2020). A new standard for the analysis and design of replication studies (with discussion). Journal of the Royal Statistical Society: Series A (Statistics in Society), 183(2), 431-448. tools:::Rd_expr_doi("10.1111/rssa.12493")

Examples

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