Given the baseline, the maximum effect and the standardized model parameters this function calculates the location and scale parameters in the model function using the maximum approach, see Pinheiro et al. (2006) for the basic idea.
model: A character string with the model name. Built-in models have their full parameterization derived internally. For user-defined models, it is assumed that a function named as "Par" appended to end of model name exists (e.g., for model = "cubic", it is assumed that there is function "cubicPar" that calculates the necessary parameters; this function is assumed to have arguments "doses", "initEstim", "base", and "maxEff", in that order (see below for an example).
doses: Doses to be used in design
initEstim: Vector of guesstimates
base: Expected baseline effect
maxEff: Expected maximum change from baseline
off: Offset parameter for the linear in log model (default 1).
scal: Scale parameter for the beta model (default: 20 perc. larger than maximum dose).
Returns
Vector containing all model parameters.
References
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
fullMod
Examples
doses <- c(0,10,25,50,100,150)getPars("emax", doses,25,0,0.4)getPars("logistic", doses, c(50,10.88111),0,0.4)# compare JBS 16, p.650getPars("betaMod", doses, initEstim = c(0.33,2.31), base =0, maxEff =0.4)#example for user model userMod <-function(dose, e0, eMax, ed50, h){ e0 + eMax *( dose^h /(ed50^h + dose^h))}# function to return location and scale parameters userModPar <-function(dose, initEstim, base, maxEff){# function to get linear parameters # ed50 parameter assumed to be first in initEstim ed50 <- initEstim[1] h <- initEstim[2] dmax <- max(dose) emax <- maxEff*(ed50^h+dmax^h)/dmax^h
c(base, emax, initEstim)}getPars("userMod", doses, initEstim = c(50,2), base =0, maxEff =1)