compute_ol {BCEA} | R Documentation |

## Compute Opportunity Loss

### Description

The difference between the maximum utility computed for the current
parameter configuration (e.g. at the current simulation) `U^*`

and the current
utility of the intervention associated with the maximum utility overall.

### Usage

```
compute_ol(Ustar, U, best)
```

### Arguments

`Ustar` |
Maximum utility value (sim x k) |

`U` |
Net monetary benefit (sim x k x interv) |

`best` |
Best intervention for given willingness-to-pay (k) |

### Details

In mathematical notation,

`\textrm{OL}(\theta) := U^*(\theta) - U(\theta^\tau)`

where `\tau`

is the intervention associated with the overall maximum utility
and `U^*(\theta)`

is the maximum utility value among the comparators in the given simulation.
The opportunity loss is a non-negative quantity, since `U(\theta^\tau)\leq U^*(\theta)`

.

In all simulations where the intervention is more
cost-effective (i.e. when incremental benefit is positive), then `\textrm{OL}(\theta) = 0`

as there would be no opportunity loss, if the parameter configuration were the
one obtained in the current simulation.

### Value

Array with dimensions (sim x k)

### See Also

*BCEA*version 2.4.6 Index]