AGSDest (version 2.3.4)

seqconfint: Calculates confidence interval

Description

Calculates the repeated confidence bound or the confidence bound based on the stage-wise ordering of a GSD or a AGSD

Usage

seqconfint(object, type = c("r", "so"), level = NULL)

Arguments

object

object of the class GSTobj or of the class AGSTobj

type

confidence type: repeated "r", stage-wise ordering "so" or both "b" (default: "b")

level

type I error rate (default: NULL)

Value

The function seqconfint returns according to the class of object the classical or adaptive confidence bound. If object has class GSTobj the classical confidence bound is calculated. If the parameter value has the class AGSTobj the adaptive confidence bound is calculated.

The calculated confidence bounds are saved as:

cb.r

repeated confidence bound

cb.so

confidence bound based on the stage-wise ordering

If the level is set to 0.5, the calculated point estimates are:

est.mu

Median unbiased point estimate, based on the stage-wise ordering

est.cons

Flexible, but conservative repeated point estimate

Details

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 confidence interval (classical or adaptive).

If object has class GSTobj, then a confidence bound for a classical GSD is calculated. type defines the type of confidence interval that is calculated

"r"	Repeated confidence bound for a classical GSD
"so"	Confidence bound for a classical GSD based on the stage-wise ordering

If object has class AGSTobj, then a confidence bound for a GSD with design adaptation is calculated. type defines the type of confidence interval that is calculated

"r"	Repeated confidence bound for a GSD with design adaptations
"so"	Confidence bound for a GSD with design adaptation based on the stage-wise ordering

By setting level to the value 0.5 the conservative point estimate is calculated. Default is the level of the primary trial.

References

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.

See Also

AGSTobj, GSTobj

Examples

# NOT RUN {
##The following calculates the repeated confidence bound of a group sequential trial

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))
seqconfint(GST, type="r")

##The confidence bound based on the stage-wise ordering of a group sequential trial is calculated by

seqconfint(GST, type="so")

##The repeated confidence interval at the earlier stage T=1 where the
##trial stopping rule is not met.

seqconfint(as.GST(GSD, GSDo=list(T=1, z=0.7)), type="r")

##The repeated confidence bound and the confidence bound
##based on the stage-wise ordering 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)
seqconfint(AGST)

##The repeated confidence interval at the earlier stage T=2 where the
##trial stopping rule is not met.

seqconfint(as.AGST(pT, iD, sT, sTo=list(T=2, z=1.7)), type="r")

# }
# NOT RUN {
  ##If the stage-wise adjusted confidence interval is calculated at this stage,
  ##the function returns an error message

  seqconfint(as.AGST(pT, iD, sT, sTo=list(T=2, z=1.7)), type="so")
# }