effective_dose {drda} | R Documentation |

## Effective dose

### Description

Estimate effective doses, that is the `x`

values for which `f(x) = y`

.

### Usage

```
effective_dose(object, y, type, level)
```

### Arguments

`object` |
fit object as returned by |

`y` |
numeric vector with response levels (default 0.5). |

`type` |
character string with either "relative" (default) or "absolute". |

`level` |
level of confidence intervals (default 0.95). |

### Details

Given a fitted model `f(x; theta)`

we seek the values `x`

at which the
function is equal to the specified response values.

If responses are given on a relative scale (`type = "relative"`

), then `y`

is
expected to range in the interval `(0, 1)`

.

If responses are given on an absolute scale (`type = "absolute"`

), then `y`

is free to vary on the whole real line. Note, however, that the solution
does not exist when `y`

is not in the image of the function.

### Value

Numeric matrix with the effective doses and the corresponding
confidence intervals. Each row is associated with each value of `y`

.

### Examples

```
drda_fit <- drda(response ~ log_dose, data = voropm2)
effective_dose(drda_fit)
# relative values are given on the (0, 1) range
effective_dose(drda_fit, y = c(0.2, 0.8))
# explicitly say when we are using actual response values
effective_dose(drda_fit, y = c(0.2, 0.8), type = "absolute")
# use a different confidence level
effective_dose(drda_fit, y = 0.6, level = 0.8)
```

*drda*version 2.0.3 Index]