Based on a preplanned graphical multiple comparison procedure, construct a valid multiple level alpha test that conserves the family wise error in the strong sense regardless of any trial adaptations during an unblinded interim analysis.  Implementation of adaptive procedures is still in an early stage and may change in the near future
1 2  secondStageTest(interim, select, matchCE = TRUE, zWeights = "reject",
G2 = interim@preplanned)

interim 
An object of class 
select 
A logical vector giving specifying which hypotheses are carried forward to the second stage 
matchCE 
Logical specifying whether second stage weights should be computed proportional to corresponding PCEs 
zWeights 
Either "reject","accept", or "strict" giving the rule what should be done in cases where none of the selected hypotheses has positive second stage weight. 
G2 
An object of class 
For details see the given references.
A function of signature function(z2)
with arguments
z2
a numeric vector with second stage zscores (Zscores of
dropped hypotheses should be set no NA
)
that returns objects of class gMCPResult
.
Florian Klinglmueller float@lefant.net
Frank Bretz, Willi Maurer, Werner Brannath, Martin Posch: A graphical approach to sequentially rejective multiple test procedures. Statistics in Medicine 2009 vol. 28 issue 4 page 586604. http://www.meduniwien.ac.at/fwf_adaptive/papers/bretz_2009_22.pdf
Bretz F., Posch M., Glimm E., Klinglmueller F., Maurer W., Rohmeyer K. (2011): Graphical approaches for multiple endpoint problems using weighted Bonferroni, Simes or parametric tests  to appear.
Posch M, Futschik A (2008): A Uniform Improvement of BonferroniType Tests by Sequential Tests JASA 103/481, 299308
Posch M, Maurer W, Bretz F (2010): Type I error rate control in adaptive designs for confirmatory clinical trials with treatment selection at interim Pharm Stat 10/2, 96104
graphMCP
, doInterim
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16  ## Simple successive graph (Maurer et al. 2011)
## two treatments two hierarchically ordered endpoints
a < .025
G < simpleSuccessiveI()
## some zscores:
p1=c(.1,.12,.21,.16)
z1 < qnorm(1p1)
p2=c(.04,1,.14,1)
z2 < qnorm(1p2)
v < c(1/2,1/3,1/2,1/3)
intA < doInterim(G,z1,v)
## select only the first treatment
fTest < secondStageTest(intA,c(1,0,1,0))

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