Description Usage Arguments Value References Examples

Calibrate binomial assays, generalizing the calculation of LD50.

1 | ```
dose.p(obj, cf = 1:2, p = 0.5)
``` |

`obj` |
A fitted model object of class inheriting from |

`cf` |
The terms in the coefficient vector giving the intercept and coefficient of (log-)dose |

`p` |
Probabilities at which to predict the dose needed. |

An object of class `"glm.dose"`

giving the prediction (attribute
`"p"`

and standard error (attribute `"SE"`

) at each response
probability.

Venables, W. N. and Ripley, B. D. (2002)
*Modern Applied Statistics with S.*
Springer.

1 2 3 4 5 6 7 8 9 | ```
ldose <- rep(0:5, 2)
numdead <- c(1, 4, 9, 13, 18, 20, 0, 2, 6, 10, 12, 16)
sex <- factor(rep(c("M", "F"), c(6, 6)))
SF <- cbind(numdead, numalive = 20 - numdead)
budworm.lg0 <- glm(SF ~ sex + ldose - 1, family = binomial)
dose.p(budworm.lg0, cf = c(1,3), p = 1:3/4)
dose.p(update(budworm.lg0, family = binomial(link=probit)),
cf = c(1,3), p = 1:3/4)
``` |

```
Dose SE
p = 0.25: 2.231265 0.2499089
p = 0.50: 3.263587 0.2297539
p = 0.75: 4.295910 0.2746874
Dose SE
p = 0.25: 2.191229 0.2384478
p = 0.50: 3.257703 0.2240685
p = 0.75: 4.324177 0.2668745
```

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.