Last data update: 2014.03.03

R: as Group Sequential Trial
as.GSTR Documentation

as Group Sequential Trial

Description

Function as.GST builds a group sequential trial object

Usage

as.GST(GSD, GSDo)

Arguments

GSD

object of the class GSTobj; group sequential design

GSDo

group sequential design outcome; a list with the variables T and z; list(T = stage where trial stops, z = z-statistic at stage where trial stops)

Value

Returns a list containing the GSD and GSDo with class=GSTobj

Author(s)

Niklas Hack niklas.hack@meduniwien.ac.at and Werner Brannath werner.brannath@meduniwien.ac.at

See Also

GSTobj

Examples

GSD <- plan.GST(K=4,SF=1,phi=0,alpha=0.025,delta=6,pow=0.8,compute.alab=TRUE,compute.als=TRUE)
GSDo <- list(T=2, z=3.1)
GST <- as.GST(GSD=GSD,GSDo=GSDo)
GST

Results


R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(AGSDest)
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/AGSDest/as.GST.Rd_%03d_medium.png", width=480, height=480)
> ### Name: as.GST
> ### Title: as Group Sequential Trial
> ### Aliases: as.GST
> ### Keywords: methods
> 
> ### ** Examples
> 
> GSD <- plan.GST(K=4,SF=1,phi=0,alpha=0.025,delta=6,pow=0.8,compute.alab=TRUE,compute.als=TRUE)
> GSDo <- list(T=2, z=3.1)
> GST <- as.GST(GSD=GSD,GSDo=GSDo)
> GST
4  stage group sequential design
 alpha :  0.025   SF:  1   phi:  0   Imax:  0.22   delta:  6   cp:  0.8
                                                
Upper bounds          4.333  2.963  2.359  2.014
Lower bounds         -8.000 -8.000 -8.000 -8.000
Information fraction  0.250  0.500  0.750  1.000
                             
als   0.000 0.002 0.010 0.025
alab 10.065 3.008 0.936 0.000


group sequential design outcome:

	T:  2   z:  3.1 

> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>