BMDmarg: Marginal BMD estimation for medrc models

In daniel-gerhard/medrc: Mixed effect dose-response curves

Description

Estimates the marginal benchmark dose, conditional on the estimated variance components.

Usage

BMDmarg(object, respLev, interval = c("none", "delta", "fls", "tfls"), 
    clevel=NULL, level = ifelse(!(interval == "none"), 0.95, NULL), bmd = c("additional", "extra"), 
    background = 0.05, nGQ=5, rfinterval=c(0, 1000), display=TRUE, ...)

Arguments

object	an medrc object
respLev	a numeric vector containing the benchmark response levels
interval	character string specifying the type of confidence intervals to be supplied.
clevel	character string specifying the curve id in case on estimates for a specific curve or compound is requested. By default estimates are shown for all curves.
level	confidence level, default at 0.95
bmd	benchmark dose estimation (smallest dose resulting in a probability of an abnormal response)
background	probability of an abnormal response
nGQ	integer. Specifies the number nof nodes for Gauss-Hermite quadrature.
rfinterval	numeric vector. Interval for root finding (uniroot) to search for ED values. Default is [0, 1000].
display	logical. If TRUE results are displayed; otherwise they are not
...	additional arguments

Author(s)

Christian Ritz, Daniel Gerhard

daniel-gerhard/medrc documentation built on May 14, 2019, 3:38 p.m.