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## Illustrates the usage of gsbDesign.
## See Section 4 of the vignette JSS-gsbDesign.pdf
## for more information.
## spacify trial design
design1 <- gsbDesign(nr.stages = 4, patients = c(10, 20),
sigma = c(7, 7), criteria.success = c(0, 0.8, 7, 0.5),
criteria.futility = c(2, 0.8), prior.difference = c(3, 5, 2))
names(design1)
design2 <- gsbDesign(nr.stages = 4, patients = c(10, 20), sigma = c(7, 7),
criteria.success = c(0, 0.8, 7, 0.5), criteria.futility = c(2, 0.8),
prior.control = c(3, 5), prior.treatment = c(6, 2))
## specify calculation / simulation setup
simulation1 <- gsbSimulation(truth = c(-10, 20, 60),
type.update = "treatment effect", method = "numerical integration")
simulation1a <- gsbSimulation(truth = c(-10, 20, 60),
type.update = "treatment effect", method = "simulation",
nr.sim = 50000, warnings.sensitivity = 100, seed = "generate")
simulation2 <- gsbSimulation(truth = list(seq(-5, 5, 3), seq(0, 5, 3)),
type.update = "per arm", method = "simulation", grid.type = "table",
nr.sim = 10000, warnings.sensitivity = 500, seed = "generate")
## calculate operating characteristics
oc1 <- gsb(design1, simulation1)
names(oc1)
summ.oc1 <- summary(oc1, atDelta = c(0, 2, 7))
summary(oc1, atDelta = c(0, 2, 7))
p1 <- plot(oc1, what = "cumulative all")
print(p1)
formals(gsbDesign:::plot.gsbMainOut)$what
p2 <- plot(oc1, what = "sample size")
p3 <- plot(oc1, what = "boundary")
print(p2, position = c(0,0, 0.5, 1), more = TRUE)
print(p3, position = c(0.5, 0,1, 1), more = FALSE)
tab(oc1, what = "cumulative success", atDelta = c(0, 2, 7), digits = 4,
export = FALSE)
## calculate operating characteristics
oc2 <- gsb(design2, simulation2)
tab(oc2, what = "sample size", digits = 0)
simulation2a <- gsbSimulation(truth = c(-5, 5, 0, 5, 50),
type.update = "per arm", method = "simulation", grid.type = "plot",
nr.sim = 100000, warnings.sensitivity = 50, seed = "generate")
oc2a <- gsb(design2, simulation2a)
p12 <- plot(oc2a, what = "cumulative all", delta.grid = FALSE)
print(p12)
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