mixtox (version 1.4.0)

BMD: Calculating benchmark dose (BMD) and lower limit of benchmark dose (BMDL)

Description

Calculation of BMD and BMDL for both quantal and continuous dose responses. Six 2- or 3-paramter models ('Hill', 'Weibull', 'Logit', 'Weibull_three', 'Hill_three', 'Logit_three') were employed for quantal dose responses. Three 4-parameter models ('Weibull_four', 'Logit_four', 'Hill_four') were employed for continuous data.

Usage

BMD(object, bmr = 0.10, backg = 0, def = 'additional', eq = 'as.is', 
         sigLev = 0.05, ci = 'CI', sav = FALSE)

Arguments

object

object of class curveFit.

bmr

numeric vector of bench mark response levels for which to calculate benchmark doses (should be between 0 and 1)

backg

numeric value specifying the background level (defaults to 0)

def

character string specifiying the definition of the benchmark dose to use in the calculations. "excess" and "additional" are for binomial response whereas "relative" and "hybrid" (additive hybrid) are for continuous response.

eq

default list of equations.

sigLev

the significance level for Dunnett's test. The default is 0.05.

ci

types of confidence intervals (CI or PI).CI: non-simultaneous confidence intervals; PI: non-simultaneous prediction intervals.

sav

TRUE: save output to a default file; FALSE: output will not be saved; a custom file directory: save output to the custom file directory.

Value

bmds

values of BMDL, BMD, and BMDU.

Details

Selecting the Benchmark Response Level (BMR) (https://www.epa.gov/bmds/ benchmark-dose-bmd-methods#bmr).BMR is usually set as 0.10.

References

Benchmark Dose Technical Guidance, Risk Assessment Forum, U.S. Environmental Protection Agency, Washington, DC 20460, EPA/100/R-12/001, June 2012 Kennyp (2002). Critical Issues in Benchmark Calculations from Continuous Data. Crit. Rev. Toxicol., 32, 133-153.

Examples

# NOT RUN {
## example 1
# calcualte the BMD of heavy metal Ni(2+) on the MCF-7 cells 
x <- cytotox$Ni$x
rspn <- cytotox$Ni$y
obj <- curveFit(x, rspn, eq = 'Logit', param = c(12, 3), effv = c(0.05, 0.5), rtype = 'quantal')
BMD(obj, bmr = 0.10, backg = 0, def = 'additional', eq = 'default', sigLev = 0.05, ci = 'CI')
# }