drm: Dose-response modelling

In brechtdv/QMRA: Parametric Models for Quantitative Microbial Risk Assessment

Description

Parametric modelling of dose-response data.

Usage

drm(x, n, dose, data,
    model = c("betapoisson", "bp", 
              "exponential", "exp", 
              "loglogistic", "ll",
              "logprobit", "lp",
              "extremevalue", "ev"),
    ...)

Arguments

x	Vector of infected individuals.
n	Vector of exposed individuals.
dose	Vector of administered doses.
data	An optional data frame, containing the variables in the model. If not found in data, the variables are taken from the environment from which drm is called.
model	A character string naming the dose-response model. See details below.
...	Arguments to be passed to mle.

Details

Available models:

• Beta-Poisson: model = "betapoisson" or "bp"

• Exponential: model = "exponential" or "exp"

• Log-Logistic: model = "loglogistic" or "ll"

• Log-Probit: model = "logprobit" or "lp"

• Extreme Value: model = "extremevalue" or "ev"

Value

An object of class "drm".

Author(s)

[e-mail]

References

• Haas CN, Rose JB, Gerba CP (1999) Quantitative Microbial Risk Assessment. John Wiley & Sons, Inc.

See Also

bdrm, for Bayesian dose-response modelling

Examples

## Fit Beta-Poisson dose-response model to Campylobacter dataset
drm(x = infected, n = total, dose = dose, data = campy, model = "bp")

brechtdv/QMRA documentation built on May 13, 2019, 5:06 a.m.