PieceMCMC: Returns posterior distribution for key mixture model...

In Phase123: Simulating and Conducting Phase 123 Trials

Description

This function performs MCMC with Metropolis-Hastings-Green steps for the baseline hazard function and is used in the functions Reoptimize, SimPhase123 and SimPhase3.

Usage

PieceMCMC(Y, I, YE, YT, Doses, Dose, B, prob, MaxObs)

Arguments

Y	Patient survival or followup times.
I	Patient event indicators.
YE	Vector of indicators for patient efficacy.
YT	Vector of indicators for patient toxicity.
Doses	Vector of standardized doses given to patients.
Dose	Vector of standardized doses considered in trial.
B	Number of iterations to perform in MCMC.
prob	length(Doses) X 4 matrix containing the estimated posterior probabilities for each dose and each (Efficacy, Toxicity) outcomes.
MaxObs	length(Doses) X 4 matrix containing the maximum observed survival time we want to evaluate the means to.

Value

Returns a list containing a matrix of posterior means for each dose, regression coefficients in the cox models, locations of the split points, log hazard heights on each interval, and the number of intervals in the baseline hazard.

Examples

n=100
Y=rexp(n,1)
I = rbinom(n,1,.9)
YE = rbinom(n,1,.5)
YT = rbinom(n,1,.5)
Dose = c(1,2,3,3.5,5)
Dose=(Dose-mean(Dose))/sd(Dose)
Doses = sample(1:5,n,replace=TRUE)
Doses=Dose[Doses]
B=2000
MaxObs = matrix(rep(0,length(Dose)*4),nrow=4)
prob=matrix(rep(0,length(Dose)*4),ncol=4)
prob=prob+1/4
MaxObs=MaxObs+max(Y)
G=PieceMCMC(Y,I,YE,YT,Doses,Dose,B,prob,MaxObs)

Phase123 documentation built on May 2, 2019, 9:56 a.m.