pvalue | R Documentation |
Calculates the repeated or stage-wise adjusted p-value of a GSD or a AGSD
pvalue(object, type = c("r", "so"))
object |
object of the |
type |
p-value type: repeated "r", stage-wise ordering "so" or both "b" (default: "b") |
object
can be an object of the class
GSTobj
or an object of the class
AGSTobj
.
The function identifies the class
of the object and calculates the corresponding p-value (classical or adaptive).
If object
has class
GSTobj
, then a p-value for a classical GSD is calculated.
type
defines the type of confidence interval that is calculated
"r" | Repeated p-value for a classical GSD |
"so" | Stage-wise adjusted p-value for a classical GSD |
If object
has class
AGSTobj
, then a p-value for a GSD with design adaptation is calculated.
type
defines the type of confidence interval that is calculated
"r" | Repeated p-value for a GSD with design adaptations |
"so" | Stage-wise adjusted p-value for a GSD with design adaptations |
The function pvalue
returns according to the object
the classical or adaptive p-value for the final stage.
If the parameter value has the class
GSTobj
the classical p-value is calculated. If the
parameter value has the class
AGSTobj
the adaptive p-value is calculated.
The calculated p-values are saved as:
pvalue.r |
repeated p-value |
pvalue.so |
stage-wise adjusted p-value |
The stage-wise adjusted p-value can only be calculated at the stage where the trial stops and is only valid if the stopping rule is met.
The repeated p-value can be calculated at every stage of the trial and not just at the stage where the trial stops and is also valid if the stopping rule is not met.
For calculating the sequential p-values at stage T
the user has to specify the outcome GSDo
in the object GSTobj
or sTo
(secondary trial outcome) in the object AGSTobj
. A trial outcome is a list of the form
list=(T=stage of interim analysis, z = interim z-statistic)
; see the example below.
Niklas Hack niklas.hack@meduniwien.ac.at and Werner Brannath werner.brannath@meduniwien.ac.at
Brannath, W, Mehta, CR, Posch, M (2008) ”Exact confidence bounds following adaptive group sequential tests”, Biometrics accepted.
Jennison, C, Turnbull, BW (1989) ”Repeated confidence intervals for group sequential clinical trials”, Contr. Clin. Trials, 5, 33-45.
Mehta, CR, Bauer, P, Posch, M, Brannath, W (2007) ”Repeated confidence intervals for adaptive group sequential trials”, Statistics in Medicine, 26, 5422-5433.
Mueller, HH, Schaefer, H (2001) ”Adaptive group sequential design for clinical trials: Combining the advantages of adaptive and of classical group sequential approaches”, Biometrics, 57, 886-891.
Tsiatis,AA, Rosner,GL, Mehta,CR (1984) ”Exact confidence intervals following a group sequential test”, Biometrics, 40, 797-804.
AGSTobj
, GSTobj
##The following calculates the repeated p-value of a group sequential trial ## Not run: GSD=plan.GST(K=4,SF=1,phi=0,alpha=0.025,delta=6,pow=0.8,compute.alab=TRUE,compute.als=TRUE) GST<-as.GST(GSD=GSD,GSDo=list(T=2, z=3.1)) pvalue(GST,type="r") ##The stage-wise adjusted p-value of a group sequential trial is calculated by pvalue(GST,type="so") ##The repeated p-value at the earlier stage T=1 where the trial stopping rule is not met. pvalue(as.GST(GSD,GSDo=list(T=1,z=0.7)),type="r") ##If the stage-wise adjusted p-value is calculated at this stage, ##the function returns an error message pvalue(as.GST(GSD,GSDo=list(T=1,z=0.7)),type="so") ##The repeated and the stage-wise adjusted p-value of a ##group sequential trial after a design adaptation is calculated by pT=plan.GST(K=3,SF=4,phi=-4,alpha=0.05,delta=6,pow=0.9,compute.alab=TRUE,compute.als=TRUE) iD=list(T=1, z=1.090728) swImax=0.0625 I2min=3*swImax I2max=3*swImax sT=adapt(pT=pT,iD=iD,SF=1,phi=0,cp=0.8,theta=5,I2min,I2max,swImax) sTo=list(T=2, z=2.393) AGST<-as.AGST(pT=pT,iD=iD,sT=sT,sTo=sTo) pvalue(AGST) ##The repeated p-value at the earlier stage T=2 where the stopping rule is not met. pvalue(as.AGST(pT,iD,sT,sTo=list(T=2,z=1.7)),type="r") ##If the stage-wise adjusted p-value is calculated at this stage, ##the function returns an error message pvalue(as.AGST(pT,iD,sT,sTo=list(T=2,z=1.7)),type="so") ## End(Not run)
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