compute_EIB {BCEA} | R Documentation |

## Compute Expected Incremental Benefit

### Description

A summary measure useful to assess the potential changes in the decision under different scenarios.

### Usage

```
compute_EIB(ib)
```

### Arguments

`ib` |
Incremental benefit |

### Details

When considering a pairwise comparison
(e.g. in the simple case of a reference intervention `t = 1`

and a comparator,
such as the status quo, `t = 0`

), it is defined as the difference between the
expected utilities of the two alternatives:

`eib := \mbox{E}[u(e,c;1)] - \mbox{E}[u(e,c;0)] = \mathcal{U}^1 - \mathcal{U}^0.`

Analysis of the expected incremental benefit describes how the decision changes for different values of the threshold. The EIB marginalises out the uncertainty, and does not incorporate and describe explicitly the uncertainty in the outcomes. To overcome this problem the tool of choice is the CEAC.

### Value

Array with dimensions (interv x k)

### See Also

`ceac.plot()`

, `compute_CEAC()`

, `compute_IB()`

*BCEA*version 2.4.6 Index]