R Under development (unstable) (2023-06-26 r84605 ucrt) -- "Unsuffered Consequences" Copyright (C) 2023 The R Foundation for Statistical Computing Platform: x86_64-w64-mingw32/x64 R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > ## require("DoseFinding") > > ## ## commented out for time reasons > > ## resp <- c(1.23, 1.31, 1.32, 1.36, 1.38) > ## dose <- c(0, 1.25, 2.5, 5, 10) > ## sdev <- c(0.015, 0.014, 0.015, 0.016, 0.015) > ## V <- diag(sdev^2) > ## mods <- Mods(emax=c(2.65, 12.5), linear=NULL, linInt = c(1, 1, 1, 1), > ## logistic=c(29, 9.55), quadratic = -0.0075, > ## doses=dose) > ## mmfit <- MCPMod(dose, resp, S=V, type="general", models=mods, Delta=0.12) > ## efit <- mmfit$mods$emax > ## plot(efit, plotData = "meansCI", CI=TRUE) > ## plot(efit, plotData = "meansCI", CI=FALSE) > ## ## plot(efit, plotData = "raw") # should throw an error > ## plot(efit, plotData = "means", CI = TRUE) > ## plot(efit, plotData = "means", CI = FALSE) > ## plot(efit, plotData = "none", CI =TRUE) > ## plot(efit, plotData = "none", CI =FALSE) > > ## plot(mmfit, plotData = "meansCI", CI=TRUE) > ## plot(mmfit, plotData = "meansCI", CI=FALSE) > ## ## plot(mmfit, plotData = "raw") # should throw an error > ## plot(mmfit, plotData = "means", CI = TRUE) > ## plot(mmfit, plotData = "means", CI = FALSE) > ## plot(mmfit, plotData = "none", CI =TRUE) > ## plot(mmfit, plotData = "none", CI =FALSE) > > ## data(IBScovars) > ## models <- Mods(emax = c(0.5, 1), betaMod=c(1,1), linear = NULL, doses=c(0,4)) > ## mmfit <- MCPMod(dose, resp, data=IBScovars, models=models, Delta=0.12) > ## efit <- mmfit$mods$emax > ## plot(efit, plotData = "meansCI", CI=TRUE) > ## plot(efit, plotData = "meansCI", CI=FALSE) > ## plot(efit, plotData = "raw", CI=FALSE) > ## plot(efit, plotData = "raw", CI=TRUE) > ## plot(efit, plotData = "means", CI = TRUE) > ## plot(efit, plotData = "means", CI = FALSE) > ## plot(efit, plotData = "none", CI =TRUE) > ## plot(efit, plotData = "none", CI =FALSE) > > ## plot(mmfit, plotData = "meansCI", CI=TRUE) > ## plot(mmfit, plotData = "meansCI", CI=FALSE) > ## plot(mmfit, plotData = "raw", CI=TRUE) > ## plot(mmfit, plotData = "raw", CI=FALSE) > ## plot(mmfit, plotData = "means", CI = TRUE) > ## plot(mmfit, plotData = "means", CI = FALSE) > ## plot(mmfit, plotData = "none", CI =TRUE) > ## plot(mmfit, plotData = "none", CI =FALSE) > > ## data(IBScovars) > ## models <- Mods(emax = c(0.5, 1), betaMod=c(1,1), linInt = c(1, 1, 1, 1), > ## linear = NULL, doses=0:4) > ## anovaMod <- lm(resp~factor(dose)+gender, data=IBScovars) > ## drFit <- coef(anovaMod)[2:5] # placebo adjusted estimates at doses > ## vCov <- vcov(anovaMod)[2:5,2:5] > ## dose <- sort(unique(IBScovars$dose))[-1] > ## mmfit <- MCPMod(dose, drFit, S=vCov, type = "general", models=models, Delta=0.12, placAdj=TRUE) > ## efit <- mmfit$mods$emax > ## plot(efit, plotData = "meansCI", CI=TRUE) > ## plot(efit, plotData = "meansCI", CI=FALSE) > ## ## plot(efit, plotData = "raw", CI=FALSE) # should throw an error > ## ## plot(efit, plotData = "raw", CI=TRUE) # should throw an error > ## plot(efit, plotData = "means", CI = TRUE) > ## plot(efit, plotData = "means", CI = FALSE) > ## plot(efit, plotData = "none", CI =TRUE) > ## plot(efit, plotData = "none", CI =FALSE) > > ## plot(mmfit, plotData = "meansCI", CI=TRUE) > ## plot(mmfit, plotData = "meansCI", CI=FALSE) > ## ## plot(mmfit, plotData = "raw", CI=TRUE) # should throw an error > ## ## plot(mmfit, plotData = "raw", CI=FALSE) # should throw an error > ## plot(mmfit, plotData = "means", CI = TRUE) > ## plot(mmfit, plotData = "means", CI = FALSE) > ## plot(mmfit, plotData = "none", CI =TRUE) > ## plot(mmfit, plotData = "none", CI =FALSE) > > ## ## neurodeg example (in 0.9-6 not all means were visible) > ## doses <- c(0,1,3,10,30) > ## muH <- c(-5.099, -4.581, -3.22, -2.879, -3.52) # estimated slope > ## covH <- structure(c(0.149, 0.009, 0.009, 0.009, 0.009, 0.009, 0.149, > ## 0.009, 0.009, 0.009, 0.009, 0.009, 0.149, 0.009, > ## 0.009, 0.009, 0.009, 0.009, 0.149, 0.009, 0.009, > ## 0.009, 0.009, 0.009, 0.149), .Dim = c(5L, 5L)) > ## fit <- fitMod(doses, muH, S=covH, model="emax", type = "general") > ## plot(fit, plotData="meansCI", CI=TRUE) > > > proc.time() user system elapsed 0.12 0.01 0.14