View source: R/get.ts.ng.trt.int.oc.df.r
get.ts.ng.trt.int.oc.df | R Documentation |
Get two-sample normal-gamma interim OC curve data.frame
get.ts.ng.trt.int.oc.df( mu.0.t = 0, n.0.t = 1e-04, alpha.0.t = 0.25, beta.0.t = 1, mu.0.c = 0, n.0.c = 10, alpha.0.c = 2.5, beta.0.c = 10, Delta.lrv = 1.5, Delta.tv = 3, mu.c = 0.25, s.t = 1.5, s.c = 1.5, npointsLookup = 20, npoints = 20, n.MC.lookup = 500, n.MC = 500, tau.tv = 0.1, tau.lrv = 0.8, tau.ng = 0.65, n.int.t = c(27, 40), n.int.c = c(27, 40), final.n.t = 55, final.n.c = 55, go.thresh = 0.6, ng.thresh = 0.6, go.parallel = TRUE, cl = cl, seed = 1234, include_nogo = TRUE )
mu.0.t |
prior mean for treatment group |
n.0.t |
prior effective sample size parameter for treatment group |
alpha.0.t |
prior alpha parameter for treatment group |
beta.0.t |
prior beta parameter for treatment group |
mu.0.c |
prior mean for control group |
n.0.c |
prior effective sample size parameter for control group |
alpha.0.c |
prior alpha parameter for control group |
beta.0.c |
prior beta parameter for control group |
Delta.lrv |
TPP Lower Reference Value aka Min TPP |
Delta.tv |
TPP Target Value aka Base TPP |
mu.c |
assumed mean for control group |
s.t |
treatment standard deviation |
s.c |
control standard deviation |
npointsLookup |
number of points for lookup table |
npoints |
number of points to run simulations |
n.MC.lookup |
number of trials used for lookup table |
n.MC |
number of trials run at each point |
tau.tv |
threshold associated with Base TPP |
tau.lrv |
threshold associated with Min TPP |
tau.ng |
threshold associated with No-Go |
n.int.t |
interim sample sizes for treatment arm |
n.int.c |
interim sample sizes for control arm |
final.n.t |
final sample size: treatment arm |
final.n.c |
final sample sizE: control arm |
go.thresh |
interim predictive probability threshold for go |
ng.thresh |
interim predictive probability threshold for no-go |
go.parallel |
logical for parallel processing |
cl |
cl |
seed |
random seed |
include_nogo |
logical |
A data.frame is returned.
my.ts.ng.trt.int.oc.df <- get.ts.ng.trt.int.oc.df(npointsLookup = 2, npoints=3, n.MC.lookup=5, n.MC=5, go.parallel=FALSE)
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