bsummary {brmsmargins} | R Documentation |

## Personal Preference Based Bayesian Summary

### Description

Returns a summary of a posterior distribution for a single
parameter / value. It is based on personal preference. Notably, it does not
only use `bayestestR::describe_posterior`

, an excellent function,
because of the desire to also describe the percentage of the full posterior
distribution that is at or exceeding the value of a
Minimally Important Difference (MID). MIDs are used in clinical studies with outcome
measures where there are pre-defined differences that are considered clinically
important, which is distinct from the ROPE or general credible intervals capturing
uncertainty.

### Usage

```
bsummary(x, CI = 0.99, CIType = "HDI", ROPE = NULL, MID = NULL)
```

### Arguments

`x` |
The posterior distribution of a parameter |

`CI` |
A numeric value indicating the desired width of the credible interval.
Defaults to |

`CIType` |
A character string indicating the type of credible interval, passed on
to the |

`ROPE` |
Either left as |

`MID` |
Either left as |

### Value

A `data.table`

with the mean, `M`

- M
the mean of the posterior samples

- Mdn
the median of the posterior samples

- LL
the lower limit of the credible interval

- UL
the upper limit of the credible interval

- PercentROPE
the percentage of posterior samples falling into the ROPE

- PercentMID
the percentage of posterior samples falling at or beyond the MID

- CI
the width of the credible interval used

- CIType
the type of credible interval used (e.g., highest density interval)

- ROPE
a label describing the values included in the ROPE

- MID
a label describing the values included in the MID

### References

Kruschke, J. K. (2018). doi:10.1177/2515245918771304 “Rejecting or accepting parameter values in Bayesian estimation”

### Examples

```
bsummary(rnorm(1000))
bsummary(rnorm(1000), ROPE = c(-.5, .5), MID = c(-1, 1))
```

*brmsmargins*version 0.2.0 Index]