RunNLME {PKtools} | R Documentation |
RunNLME uses the NLME software to estimate parameters for a single dose population PK model with hierarchical data.
RunNLME(inputStructure,data, nameData)
inputStructure |
NLME-model.def |
data |
list of data files including pk data and covariate data the length of the full dataset |
nameData |
list of names, including, covnames, yvarlab, xvarlab, paramester names |
model.def is a list of the definitions of the model form, fixed and random effects, the starting values and control argument from the nlme function. The following is an example.
nameData is a list of the labels including the names of the covariates in the order they are given in the covariate dataset, y and x variable, the random parameters (reparams -should match the list for random.model in the model.def), fixed parameters (params -should match the list for fixed.model in the model.def), label for transformed parameters ( in the Theo example the model parameters are on a log scale tparam=c("log(Ka)","log(V)","log(Cl)") and the names of the variance parameters are not required for NLMEoutput.
Output datasets include the input data, the parameter estimates, covariates, model residuals at the population and individual levels,and model predicted values for the population and individual levels.
M.S. Blanchard <sblanchard@coh.org>
Pinheiro, J.C. and Bates, D.M. (2000). "Mixed-Effects Models in S and SPLUS." Springer: New York.
#NLME example library(PKtools) library(nlme) data(Theoph) Theoph<-Theoph[Theoph$Time!=0,] id<-as.numeric(as.character(Theoph$Subject)) dose<-Theoph$Dose time<-Theoph$Time conc<-round(sqrt(Theoph$conc),4) Theo<-data.frame(cbind(id,dose,time,conc)) names(Theo)<-c("id","dose","time","conc") wt.v<-Theoph$Wt data<-list(pkvar=Theo, cov=wt.v) nameData<-list(covnames=c("wt"), yvarlab="Sqrt(Theop. Conc.) (mg/L)", xvarlab="Time since dose (hrs)", reparams=c("Cl"), params=c("Ka","V", "Cl"), tparams=c("log(Ka)","log(V)","log(CL)")) model.def<-list(fixed.model=lKa+lV+lCl~1,random.model=lCl~1, start.lst=c(lKa=.3,lV=-.6,lCl=-3), form=conc~sonecpmt(dose, time, lV, lKa, lCl), control=nlmeControl(returnObject=FALSE)) MM<-RunNLME(inputStructure=model.def, data=data, nameData=nameData) MM