fullMod: Calculate location and scale parameters for candidate set of...

Description Usage Arguments Value References See Also Examples

View source: R/planMCPMod.R

Description

Calculates location and scale parameters for all models in the candidate set using the maximum approach from Pinheiro et al. (2006). This is done by repeatedly calling the getPars function.

Usage

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fullMod(models, doses, base, maxEff, off = 0.1*max(doses), scal = 1.2 * max(doses))

Arguments

models

A list specifying the candidate models. The names of the list entries should be equal to the names of the model functions. The list entries should be equal to the guesstimates

doses

Dose levels to be administered

base, maxEff

Baseline effect and maximum change from baseline to be used for calculating the location and scale parameters of the model

off

Offset parameter for the linear in log model

scal

Scale parameter for the beta model

Value

Returns an object of class fullMod, containing all parameter values for the models in a list.

References

Bornkamp B., Pinheiro J. C., Bretz, F. (2009). MCPMod: An R Package for the Design and Analysis of Dose-Finding Studies, Journal of Statistical Software, 29(7), 1–23

Pinheiro, J. C., Bornkamp, B. and Bretz, F. (2006). Design and analysis of dose finding studies combining multiple comparisons and modeling procedures, Journal of Biopharmaceutical Statistics, 16, 639–656

See Also

getPars, sampSize, powerMM, plotModels, LP

Examples

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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))
fMod <- fullMod(models, doses, base = 0, maxEff = 0.4, scal = 200)                 
plot(fMod) # automatically calls the plotModels function

Example output

Loading required package: mvtnorm
Loading required package: lattice

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