create.utility.function {bdpopt} R Documentation

## Create Utility Function For The Normal Model

### Description

Create a utility function to be used together with a normal simulation model object created using `create.normal.model` or `create.normal.model.from.file`.

### Usage

```create.utility.function(model, n.min, sig.level, safety.max, cE, cS, p,
fixed.cost, cost.per.sample)
```

### Arguments

 `model` A model object created using `create.normal.model` or `create.normal.model.from.file`. `n.min` The minimum group sample size for each phase III group trial required by the regulatory authority in order to consider market approval. `sig.level` The significance level used by the regulatory authority when performing the one-sided hypothesis tests for acceptable efficacy and safety levels in the phase III trial. `safety.max` A parameter defining the maximum safety threshold in the significance test for an acceptable safety level. `cE` A constant defining the utility gain per unit of efficacy. `cS` A constant defining the utility gain per unit of safety. The absolute value of this number defines the utility loss, and hence `cS` should typically be less than or equal to zero. `p` A number between 0 and 1 which weighs the relative contribution of the observed responses and the true population means to the utility upon regulatory approval. A value of 1 corresponds to no contribution made by the population means. `fixed.cost` The fixed cost of performing the phase III trials. `cost.per.sample` The cost per observation in the phase III trials.

### Details

The utility function has the form:

`RA.decision * gain - trial.cost`

where

```gain = p * (cE * mean(YE) + cS * mean(YS)) + (1 - p) * (cE * mean(muE) + cS * mean(muS))```

`trail.cost = fixed.cost + cost.per.sample * k.III * n.III`

### Value

An R function to be used together with `model` when calling `eval.on.grid`, `fit.gpr`, `fit.loess` and `optimise.eu`.

### Author(s)

Sebastian Jobjörnsson jobjorns@chalmers.se

[Package bdpopt version 1.0-1 Index]