drc_model: Wrapper for DRC Dose Response Models

In maomlab/BayesPharma: Tools for Bayesian Analysis of Non-Linear Pharmacology Models

Wrapper for DRC Dose Response Models

Description

The Dose Response Curve (drc) package supports regression models for sigmoidal and other functional forms. This wrapper sets up a similar model to the sigmoid_model.

Usage

drc_model(
  data,
  formula = response ~ log_dose,
  fct = drc::L.4(fixed = c(NA, NA, NA, NA), names = c("hill", "bottom", "top", "ec50")),
  ...
)

Arguments

data	data.frame
formula	formula formula relating the response to the log_dose, if the drc::L.4 sigmoid link function is used or dose if the drc::LL.4 log-linear sigmoid link functions used with the fct argument.
fct	Boltzmann non-linear link function. Default is the 4 parameter log-linear sigmoid equation, drc::L.4, where all parameters are to be estimated. To fix a subset them, set the parameters to constant values.
...	additional arguments passed to drc::drm

Value

An object of (S3) class drc from the drc package.

Examples

## Not run: 
BayesPharma::drc_model(
  data = tibble::tibble(
    log_dose = seq(-7, -5, length.out = 20),
    mean_response = BayesPharma::sigmoid(
      ac50 = -6, hill = -1, top = 1, bottom = 0, log_dose = log_dose),
    response = stats::rnorm(n = 20, mean = 0, sd = 0.2)))

## End(Not run)

maomlab/BayesPharma documentation built on Aug. 24, 2024, 8:45 a.m.