## settings for 1dCFO
nsimu <- 5; ncohort <- 12; cohortsize <- 3; init.level <- 1
p.true <- c(0.02, 0.05, 0.20, 0.28, 0.34, 0.40, 0.44); target <- 0.2
assess.window <- 3; accrual.rate <- 2; tte.para <- 0.5; accrual.dist <- 'unif'
## summarize the object returned by CFO.next()
decision <- CFO.next(target = 0.2, cys = c(0, 1, 0), cns = c(3, 6, 0), currdose = 3)
print(decision)
## summarize the object returned by lateonset.next()
enter.times<- c(0, 0.266, 0.638, 1.54, 2.48, 3.14, 3.32, 4.01, 4.39, 5.38, 5.76,
6.54, 6.66, 6.93, 7.32, 7.65, 8.14, 8.74)
dlt.times<- c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0.995, 0, 0, 0, 0, 0, 0, 0, 2.58)
current.t<- 9.41; ndose = 7
doses<-c(1, 1, 1, 2, 2, 2, 3, 3, 3, 4, 4, 4, 3, 3, 3, 4, 4, 4)
decision <- lateonset.next(design = 'f-aCFO', target, ndose, currdose = 4, assess.window,
enter.times, dlt.times, current.t, doses)
print(decision)
## summarize the object returned by CFO.selectmtd()
selmtd <- CFO.selectmtd(target=0.2, npts=c(3,3,27,3,0,0,0), ntox=c(0,0,4,2,0,0,0))
print(selmtd)
## summarize the object returned by CFO.simu()
aCFOtrial <- CFO.simu(design = 'aCFO', target, p.true, init.level, ncohort, cohortsize, seed = 1)
print(aCFOtrial)
# \donttest{
# This test may take longer than 5 seconds to run
# It is provided for illustration purposes only
# Users can run this code directly
## summarize the object returned by lateonset.simu()
faCFOtrial <- lateonset.simu (design = 'f-aCFO', target, p.true, init.level,
ncohort, cohortsize, assess.window, tte.para, accrual.rate, accrual.dist, seed = 1)
print(faCFOtrial)
## summarize the object returned by CFO.oc()
faCFOoc <- CFO.oc (nsimu, design = 'f-aCFO', target, p.true, init.level, ncohort, cohortsize,
assess.window, tte.para, accrual.rate, accrual.dist, seeds = 1:nsimu)
print(faCFOoc)
## settings for 2dCFO
p.true <- matrix(c(0.05, 0.10, 0.15, 0.30, 0.45,
0.10, 0.15, 0.30, 0.45, 0.55,
0.15, 0.30, 0.45, 0.50, 0.60),
nrow = 3, ncol = 5, byrow = TRUE)
cns <- matrix(c(3, 3, 0,
0, 6, 0,
0, 0, 0),
nrow = 3, ncol = 3, byrow = TRUE)
cys <- matrix(c(0, 1, 0,
0, 2, 0,
0, 0, 0),
nrow = 3, ncol = 3, byrow = TRUE)
currdose <- c(2,3); target <- 0.3; ncohort <- 12; cohortsize <- 3
## summarize the object returned by CFO2d.next()
decision <- CFO2d.next(target, cys, cns, currdose = currdose, seed = 1)
print(decision)
## summarize the object returned by CFO2d.selectmtd()
ntox <- matrix(c(0, 0, 2, 0, 0, 0, 2, 7, 0, 0, 0, 2, 0, 0, 0), nrow = 3, ncol = 5, byrow = TRUE)
npts <- matrix(c(3, 0, 12, 0, 0, 3, 12, 24, 0, 0, 3, 3, 0, 0, 0), nrow = 3, ncol = 5, byrow = TRUE)
selmtd <- CFO2d.selectmtd(target=0.3, npts=npts, ntox=ntox)
print(selmtd)
## summarize the object returned by CFO2d.simu()
CFO2dtrial <- CFO2d.simu(target, p.true, init.level = c(1,1), ncohort, cohortsize, seed = 1)
print(CFO2dtrial)
## summarize the object returned by CFO2d.oc()
CFO2doc <- CFO2d.oc(nsimu = 5, target, p.true, init.level = c(1,1), ncohort, cohortsize,
seeds = 1:5)
print(CFO2doc)
## summarize the object returned by CFOeff.next()
decision <- CFOeff.next(target=0.4,axs=c(3,1,7,11,26),ays=c(0,0,0,0,6),
ans= c(6, 3, 12, 17, 36), currdose = 3, mineff = 0.3)
print(decision)
## summarize the object returned by CFOeff.simu()
target <- 0.30; mineff <- 0.30
prior.para = list(alp.prior = target, bet.prior = 1 - target,
alp.prior.eff = 0.5, bet.prior.eff = 0.5)
p.true=c(0.05, 0.07, 0.1, 0.12, 0.16)
pE.true=c(0.35, 0.45, 0.5, 0.55, 0.75)
result <- CFOeff.simu(target, p.true, pE.true, ncohort, init.level, cohortsize,
prior.para, mineff = mineff, seed = 1)
print(result)
## summarize the object returned by CFOeff.oc()
nsimu = 10
result <- CFOeff.oc(target, p.true, pE.true, prior.para,
init.level,cohortsize, ncohort, nsimu, mineff = mineff, seeds = 1:nsimu)
print(result)
# }
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