eiaPred: Mixture Effect Predicted by IA at Particular Concentration of a Mixture

Description

According to the fitted concentration-response information of mixtures. The concentration (e.g., ECx) that causes certain effect in the mixture will be calculated. eiaPred will predict how much effect will be caused at those concentrations according to independent action. The individual concentration-responses should be fitted only based on the following six models: Hill, Weibull, Logit, BCW, BCL, and GL.

Usage

eiaPred(effv, sgl, mix, pctMix, sav = FALSE)

Arguments

effv

numeric vector with single or multiple effect values (0 ~ 1).

sgl

A list with sgl$model and sgl$param. sgl$model is character vector of equations used to fit the concentration-response data of individual chemicals: Hill, Weibull, Logit, BCW, BCL, GL. sgl$param is numeric matrix of fitting coefficients with rownames (selected equations) and colnames (Alpha, Beta, and Gamma). For equations with only two parameters, Gamma can be set as zero or any other numeric value.

mix

A list with mix$model and mix$param. mix$model is character vector of equations used to fit the concentration-response data of mixtures: Hill, Weibull, Logit, BCW, BCL, GL. mix$param is numeric matrix of fitting coefficients of mixtures' concentration-response data with rownames ( equations) and colnames (Alpha, Beta, and Gamma). For equations with two parameters, Gamma can be set as zero or any other numeric value.

pctMix

A numeric matrix, the concentration ratio (percent) of every component in the mixture.

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

A numeric matrix of predicted effects

Details

eiaPred calculate the effect concentrations based on the fitted concentration-response information of the mixture according to the input effects effv (e.g., 0.05 and 0.5). The concentration of individual component $c_i$ is computed based on mixture's ECx and the proportion of component in the mixture $p_i$. Then the IA effect will be calculated based on the independent action.

Examples

Run this code

# NOT RUN {
## example 1
# predict the IA predicted response (cytotoxicity) at the concentrations that cause 10% and 50% 
# effect of an mixture. 
# each mixture contains eight components. Totally, there are 10 mixtures designed by the udcr.

sgl <- cytotox$sgl
mix <- cytotox$udcr.mix
pct <- cytotox$udcr.pct
eiaPred(effv = c(0.1, 0.5), sgl, mix, pct)

## example 2
# predict the IA predicted response at the concentrations that cause 5% and 50% effect 
# of antibiotic mixtures.
# each mixture contains eight components. Totally, there are 2 mixtures designed by the eecr.

sgl <- antibiotox$sgl
mix <- antibiotox$eecr.mix
pct <- antibiotox$eecr.pct
eiaPred(effv = c(0.05, 0.5), sgl, mix, pct)

## example 2
# predict the IA predicted response at the concentrations that cause 5%, 10%, 20%, and 
# 50% effect of antibiotic mixtures.
# each mixture contains eight components. Totally, there are 10 mixtures designed by the udcr.

sgl <- antibiotox$sgl
mix <- antibiotox$udcr.mix
pct <- antibiotox$udcr.pct
eiaPred(effv = c(0.05, 0.10, 0.20, 0.5), sgl, mix, pct)
# }