rasterROE {bayesROE} | R Documentation |

## Bayesian Regions of Evidence Raster Plot

### Description

Compute and visualize the Bayesian Regions of Evidence (Raster), that is, the set of normal priors for an effect size which - when combined with the observed data - lead to a specified posterior probability for the effect size being more extreme than a specified minimally relevant effect size.

### Usage

```
rasterROE(
ee,
se,
delta = 0,
alpha = 0.025,
type = "threshold",
larger = TRUE,
meanLim = c(-3 * abs(ee), 3 * abs(ee)),
sdLim = c(0, 5 * se),
nGrid = 200,
cols = NULL,
cols_alpha = 1,
add = FALSE
)
```

### Arguments

`ee` |
Effect estimate. |

`se` |
Standard error of effect estimate. |

`delta` |
Minimally relevant effect size. Defaults to zero. Can also be a vector of numerical values to representing different regions. |

`alpha` |
Posterior probability that the effect size is less extreme than delta. Defaults to 0.025. Can also be a vector of numerical values representing different regions. |

`type` |
Character indicating if regions of evidence should be constructed for a non-inferiority claim using the first element of delta and all elements of alpha ("threshold"), for a non-inferiority claim using the all elements of delta and the first element of alpha ("probability"), for an equivalence claim using the first two elements of delta and all elements of alpha ("equivalence"), or for a prior-data conflict using only the first element of alpha ("conflict"). Defaults to "threshold". |

`larger` |
Logical indicating if effect size should be larger (TRUE) or smaller (FALSE) than delta. Ignored when type = "equivalence" or type = "conflict". Defaults to TRUE. |

`meanLim` |
Limits of prior mean axis. |

`sdLim` |
Limits of prior standard deviation axis. |

`nGrid` |
Resolution of grid points (on both axes). Defaults to 200. |

`cols` |
Character containing the HEX color code of the upper and lower region of evidence, respectively. Defaults to NULL, which triggers automated color picking by calling ggplot2:scale_fill_viridis_d() |

`cols_alpha` |
Numeric value indicating the relative opacity of any region of evidence (alpha channel). Defaults to 1 (no transparency). |

`add` |
Logical indicating if a separate geom_raster layer should be created that can be added to an existing plot (TRUE), or if an entire regions of plot should be created (FALSE). Defaults to FALSE. |

### Value

A bayesROE object (a list containing the ggplot object, the data for the plot, and the empty tipping point function)

### References

Hoefler, M., Miller, R. (2022, April 04). Bayesian regions of evidence (for normal distributions). doi:10.31234/osf.io/mg23h

### Examples

```
## data with p < 0.025 for H0: delta < 0, but p > 0.025 for H0: delta < 0.3
d <- 0.4
d_se <- 0.1
delta <- c(0, 0.3)
rasterROE(ee = d, se = d_se, delta = delta, meanLim = c(-1, 1))
## reproducing Figure 3 from Hoefler & Miller (2023)
ee <- 9
se <- 3.9
delta <- c(0, 3.75)
rasterROE(ee = ee, se = se, delta = delta, alpha = 0.05)$plot +
ggplot2::annotate(geom = "point", y = ee, x = se, shape = 4)
ggplot2::coord_flip(xlim = c(0, 12), ylim = c(-5, 10))
```

*bayesROE*version 0.2 Index]