modelMeans: Calculate mean vectors for a given candidate set

In MCPMod: Design and Analysis of Dose-Finding Studies

Description

Calculates the mean or standardized mean vectors for a candidate set of models. This function is mainly for internal use.

Usage

modelMeans(models, doses, std = TRUE, off = 0.1 * max(doses),
           scal = 1.2 * max(doses))

Arguments

models	A list of candidate models, or the output of the fullMod function (depending on the value of std).
doses	A numeric vector giving the doses to be administered.
std	Logical indicating whether standardized or non-standardized version of model function should be used.
off	Offset parameter for linear in log model.
scal	Scale parameter for beta model.

Value

Matrix with standardized or non-standardized model means.

Examples

doses <- c(0, 10, 25, 50, 100, 150)                                        
models <- list(linear = NULL, emax = c(25),                                
               logistic = c(50, 10.88111), exponential = c(85),            
               betaMod = matrix(c(0.33, 2.31, 1.39, 1.39), byrow=TRUE,nrow=2))
modelMeans(models, doses, std = TRUE)

# now non-standardized means
Models <- fullMod(models, doses, base = 0, maxEff = 0.4, scal = 200)                 
modelMeans(Models, doses, std = FALSE)

MCPMod documentation built on March 26, 2020, 7:28 p.m.