nfa.Rd
Neurotoxicity test using a network formation assay studying the inhibition of network formation at acrylamide exposure.
data(nfa)
A data frame with 45 observations on the following 4 variables.
chip
chip ID
conc
7 concentrations of acrylamide, ranging from 0-5mM
experiment
factor with levels 1 or 2 denoting two consecutive experiments
response
Number of connections [%]
Frimat, JP, Sisnaiske, J, Subbiah, S, Menne, H, Godoy, P, Lampen, P, Leist, M, Franzke, J, Hengstler, JG, van Thriel, C, West, J. The network formation assay: a spatially standardized neurite outgrowth analytical display for neurotoxicity screening. Lab Chip 2010; 10:701-709.
# NOT RUN { data(nfa) ggplot(nfa, aes(x=log(conc), y=response, colour=experiment)) + geom_point() # starting values for fixed effects fix <- coefficients(drm(response ~ conc, fct=LL.4(), data=nfa)) # starting values for random experiment effects rexp <- drm(response ~ conc, curveid=experiment, fct=LL.4(), data=nfa) cmatexp <- matrix(coefficients(rexp), ncol=4) mexp <- apply(cmatexp, 2, mean) names(mexp) <- letters[2:5] rmatexp <- t(apply(cmatexp, 1, function(x) x-mexp)) rownames(rmatexp) <- levels(nfa$experiment) colnames(rmatexp) <- letters[2:5] start <- list(fixed=fix, random=list(experiment=rmatexp[,3, drop=FALSE])) ## set of nonlinear mixed models nfa.LL4.mixed <- medrm(response ~ conc, fct=LL.4(), data=nfa, random=d ~ 1 | experiment, start=start) nfa.LN4.mixed <- medrm(response ~ conc, fct=LN.4(), data=nfa, random=d ~ 1 | experiment, start=start) nfa.W14.mixed <- medrm(response ~ conc, fct=W1.4(), data=nfa, random=d ~ 1 | experiment, start=start) nfa.W24.mixed <- medrm(response ~ conc, fct=W2.4(), data=nfa, random=d ~ 1 | experiment, start=start) ## information criteria AIC(nfa.LL4.mixed, nfa.LN4.mixed, nfa.W14.mixed, nfa.W24.mixed) ## BMDL estimation for BMR 1, 5, 10, 20 mmaBMD(nfa.LL4.mixed, nfa.LN4.mixed, nfa.W14.mixed, nfa.W24.mixed, respLev=c(1,5,10,20), interval = "buckland", bmd = "additive") # }