ssdBFr {BayesRepDesign} | R Documentation |
This function computes the standard error required to achieve replication success with a certain probability and based on the replication Bayes factor under normality. The replication Bayes factor is assumed to be oriented so that values below one indicate replication success, whereas values above one indicate evidence for the null hypothesis.
ssdBFr(
level,
dprior,
power,
searchInt = c(.Machine$double.eps^0.5, 2),
paradox = TRUE
)
level |
Bayes factor level 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 |
Returns an object of class "ssdRS"
. See ssd
for
details.
Samuel Pawel
Pawel, S., Consonni, G., and Held, L. (2022). Bayesian approaches to designing replication studies. arXiv preprint. doi:10.48550/arXiv.2211.02552
Verhagen, J. and Wagenmakers, E. J. (2014). Bayesian tests to quantify the result of a replication attempt. Journal of Experimental Psychology: General, 145:1457-1475. doi:10.1037/a0036731
Ly, A., Etz, A., Marsman, M., and Wagenmakers, E.-J. (2018). Replication Bayes factors from evidence updating. Behavior Research Methods, 51(6), 2498-2508. doi:10.3758/s13428-018-1092-x
## specify design prior
to1 <- 0.2
so1 <- 0.05
dprior <- designPrior(to = to1, so = so1, tau = 0.03)
ssdBFr(level = 1/10, dprior = dprior, power = 0.8)