drmMMRE: Dose response modeling with hierarchical variance structure

In DoseResponse/bmd: Benchmark dose estimation for dose-response data

Dose response modeling with hierarchical variance structure

Description

Fits a meta-analytic hierarchical dose-response model.

Usage

drmMMRE(formula, exp_id, data, fct, type = c("continuous", "binomial"))

Arguments

formula	a symbolic description of the model to be fit of the form 'response ~ dose'
exp_id	the name of the column in the data set that specifies the hierarchical structure of the data
data	a data frame containing the variables in the model.
fct	a list with three or more elements specifying the non-linear function, the accompanying self starter function, the names of the parameter in the non-linear function and, optionally, the first and second derivatives as well as information used for calculation of ED values. Currently available functions include, among others, the four- and five-parameter log-logistic models LL.4, LL.5 and the Weibull model W1.4. Use drc::getMeanFunctions for a full list.
type	a character string specifying the distribution of the data. The default is "continuous", corresponding to assuming a normal distribution. "binary" imply a binomial distribution.

Details

The aim to provide an R package calculating the benchmark dose (BMD) and the lower limit of the corresponding 95% confidence interval (BMDL) for continuous and quantal dose-response data for a range of dose-response models based on the available definitions of the benchmark dose concepts.

Fitting the meta-analytic model relies on a multivariate meta-analytic model provided by the function rma.mv in the "metafor" package, which can be installed by running remotes::install_github("wviechtb/metafor")

Viechtbauer, W. (2010). Conducting meta-analyses in R with the metafor package. Journal of Statistical Software, 36(3), 1-48. doi:10.18637/jss.v036.i03

Value

meta-analytic dose-response model with a hierarchical variance structure of class drcMMRE.

The primary objective is to use this model for benchmark dose estimation based on dose-response data with a heterogeneous variance structure.

Author(s)

Signe M. Jensen and Jens Riis Baalkilde

Examples

library(drc)
library(drcData)
library(metafor)
library(bmd)

set.seed(1)
data0 <- data.frame(x = rep(drcData::ryegrass$conc, 2),
                    y = rep(drcData::ryegrass$rootl, 2) +
                      c(rnorm(n = nrow(drcData::ryegrass), mean = 2, sd = 0.5),
                        rnorm(n = nrow(drcData::ryegrass), mean = 2.7, sd = 0.7)),
                    EXP_ID = rep(as.character(1:2), each = nrow(drcData::ryegrass)))

modMMRE <- drmMMRE(y~x, exp_id = EXP_ID, data = data0, fct = LL.4())
bmd(modMMRE, bmr = 0.1, backgType = "modelBased", def = "relative")

DoseResponse/bmd documentation built on July 4, 2025, 11:20 p.m.