ssdEqu {BayesRepDesign} | R Documentation |

## Sample size determination for replication success based on effect size equivalence

### Description

This function computes the standard error required to achieve replication success with a certain probability and based on effect size equivalence of original and replication effect size. Effect size equivalence is defined by the confidence interval for the difference between the original and replication effect sizes falling within an equivalence region around zero defined by the specified margin.

### Usage

```
ssdEqu(level, dprior, power, margin, searchInt = c(0, 2))
```

### Arguments

`level` |
1 - confidence level of confidence interval for effect size difference |

`dprior` |
Design prior object |

`power` |
Desired probability of replication success |

`margin` |
The equivalence margin > 0 for the symmetric equivalence region around zero |

`searchInt` |
Interval for numerical search over replication standard errors |

### 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

Anderson, S. F. and Maxwell, S. E. (2016). There's more than one way to conduct a replication study: Beyond statistical significance. Psychological Methods, 21(1), 1-12. doi:10.1037/met0000051

### Examples

```
## specify design prior
to1 <- 0.2
so1 <- 0.05
dprior <- designPrior(to = to1, so = so1, tau = 0.05)
ssdEqu(level = 0.1, dprior = dprior, power = 0.8, margin = 0.2)
```

*BayesRepDesign*version 0.42 Index]