plotSimulDRM: plot results of the simulation study

In clustDRM: Clustering Dose-Response Curves and Fitting Appropriate Models to Them

Description

a function to make a heatmap of the simulation results for tyhe given measure.

Usage

plotSimulDRM(simulDRMobj, quantity2Plot = c("mean", "bias", "mse",
  "variance", "relativeBias", "absBias", "absRelativeBias"))

Arguments

simulDRMobj	output of simulEvalDRM function
quantity2Plot	single string, the measure which should be plotted. Available choices are: c("mean", "bias", "mse", "variance", "relativeBias", "absBias", "absRelativeBias")

Value

a heatmap

Author(s)

Vahid Nassiri and Yimer Wasihun.

Examples

## gnerating data, a sample of size 20
set.seed(11)
doses2Use <-  c(0, 5, 20)
numRep2Use <- c(3, 3, 3)
generatedData <- cbind(rep(1,sum(numRep2Use)),
MCPMod::genDFdata("logistic",c(5, 3, 10, 0.05), doses2Use,
 numRep2Use, 1), 
		matrix(rnorm(1*sum(numRep2Use)), sum(numRep2Use), 1))
colnames(generatedData) <- c("ID", "dose", "response", "x1")
for (iGen in 2:20){
genData0 <- cbind(rep(iGen,sum(numRep2Use)), 
MCPMod::genDFdata("logistic",c(5, 3, 10, 0.05), doses2Use, 
numRep2Use, 1), 
			matrix(rnorm(1*sum(numRep2Use)), sum(numRep2Use), 1))
	colnames(genData0) <- c("ID", "dose", "response", "x1")
	generatedData <- rbind(generatedData, genData0)
}
simRes <- simulEvalDRM (pilotData = 
generatedData[generatedData$ID == 2, c(2,3)], 
doseLevels = c(0, 4, 20), 
		numReplications = c(6, 3, 3), numSim = 10, 
standardDeviation = 1, EDp = 0.5,
		funcList = c("linlog", "emax", "sigEmax", "logistic"))
# plot the simulated results
plotSimulDRM(simRes, quantity2Plot = "mse")

clustDRM documentation built on May 2, 2019, 5:07 a.m.