porsMeta {BayesRepDesign} | R Documentation |
This function computes the probability to achieve replication success on statistical significance of the fixed-effects meta-analytic effect estimate obtained from combining original and replication effect estimates.
porsMeta(level, dprior, sr)
level |
Significance level for p-value of the meta-analytic effect estimate (one-sided and in the same direction as the original effect estimate) |
dprior |
Design prior object |
sr |
Replication standard error |
The probability to achieve replication success
Samuel Pawel
Pawel, S., Consonni, G., and Held, L. (2022). Bayesian approaches to designing replication studies. arXiv preprint. doi:10.48550/arXiv.2211.02552
## specify design prior
to1 <- 2
so1 <- 1
dprior <- designPrior(to = to1, so = so1, tau = 0.1)
porsMeta(level = 0.025^2, dprior = dprior, sr = c(0.2, 0.1))