ssdSig {BayesRepDesign} | R Documentation |

## Sample size determination for replication success based on significance

### Description

This function computes the standard error required to achieve replication success with a certain probability and based on statistical significance of the replication effect estimate.

### Usage

```
ssdSig(level, dprior, power)
```

### Arguments

`level` |
Significance level for the replication effect estimate (one-sided and in the same direction as the original effect estimate) |

`dprior` |
Design prior object |

`power` |
Desired probability of replication success |

### 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

### Examples

```
## specify design prior
to1 <- 2
so1 <- 0.5
dprior <- designPrior(to = to1, so = so1, tau = 0.1)
ssdSig(level = 0.025, dprior = dprior, power = 0.9)
```

[Package

*BayesRepDesign*version 0.42 Index]