sim.plot: Generate plots for estimated percent allocation and response...

In iAdapt: Two-Stage Adaptive Dose-Finding Clinical Trial Design

Description

Generate plots for estimated percent allocation and response per dose.

Usage

sim.plot(sims)

Arguments

sims	output from sim.trials

Value

Error plots of estimated (1) percent allocation per dose, and (2) estimated response per dose.

Examples

# Number of pre-specified dose levels
dose <- 5 

# Vector of true toxicities associated with each dose
dose.tox <- c(0.05, 0.10, 0.20, 0.35, 0.45)       

# Acceptable (p_yes) and unacceptable (p_no) DLT rates used for establishing safety
p_no <- 0.40                                     
p_yes <- 0.15    

# Likelihood-ratio (LR) threshold
K <- 2                                          

# Cohort size used in stage 1
coh.size <- 3 

# Vector of true mean efficacies per dose (here mean T-cell persistence per dose (%))
m <- c(5, 15, 40, 65, 80)   # MUST BE THE SAME LENGTH AS dose.tox                  

# Efficacy (equal) variance per dose
v <- rep(0.01, 5) 

# Total sample size (stages 1&2)                            
N <- 25                                        

# Stopping rule
stop.rule <- 9   


numsims = 100

set.seed(1)
simulations = sim.trials(numsims = numsims, dose, dose.tox, p1 = p_no, p2 = p_yes, 
                         K, coh.size, m, v, N, stop.rule = stop.rule, cohort = 1, 
                         samedose = TRUE, nbb = 100)
                         
# sim.plot(simulations)

iAdapt documentation built on Aug. 6, 2021, 9:08 a.m.