View source: R/return.ts.bin.int.predprob.table.r
return.ts.bin.int.predprob.table | R Documentation |
Return two-sample binary predictive probability table
return.ts.bin.int.predprob.table( a.con = 0.5, b.con = 0.5, a.trt = 0.5, b.trt = 0.5, Delta.lrv = 0.08, Delta.tv = 0.08, tau.tv = 0.7, tau.lrv = 0.7, tau.ng = 0, n.int.con = 5, n.int.trt = 5, n.trt = 10, n.con = 10, p.con = 0.2, p.trt = 0.2 + seq(0, 0.5, 0.1), studyend = NULL, goparallel = FALSE )
a.con |
prior alpha parameter for control group |
b.con |
prior beta parameter for control group |
a.trt |
prior alpha parameter for treatment group |
b.trt |
prior alpha parameter for treatment group |
Delta.lrv |
TPP Lower Reference Value aka Min TPP |
Delta.tv |
TPP Target Value aka Base TPP |
tau.tv |
threshold associated with Base TPP |
tau.lrv |
threshold associated with Min TPP |
tau.ng |
threshold associated with No-Go |
n.int.con |
sample size for control group at interim |
n.int.trt |
sample size for treatment group at interim |
n.trt |
sample size for control group at interim |
n.con |
sample size for treatment group at interim |
p.con |
probability of success for control group |
p.trt |
probability of success for treatment group |
studyend |
keep null |
goparallel |
Option to use parallel computing |
A data.frame is returned
Greg Cicconetti
my.ts.bin.int.predprob.table <- return.ts.bin.int.predprob.table()
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