Lan-DeMets refined secondary boundaries, and nominal significance for the secondary endpoint are calculated by using the error spending approach.
type I error probability.
vector of relative information levels. The last element in the vector is 1.
type of primary boundary,
type of secondary boundary,
computing paramter, number of replica, a vector of four numbers.
computing paramter, a pair of numbers containing the end-points of the interval to be searched for the root.
This function uses the Lan-DeMets error spending approach,
and gives a list including refined secondary boundary and the nominal significance for the secondary endpoint.
There are two computing parameters
nRepVec includes four numbers:
nRepVec is the number of replica for calculating primary boundaries,
nRepVec is the number of replica for searching the location of peak,
nRepVec is the number of replica for calculating secondary boundaries,
nRepVec is the number of replica for calculating the nominal significance.
initIntvl contains the end-points of the interval to be searched for the root.
For Lan-DeMets error spending approach, the lower end point should choose a number slightly less than 1,
and the upper end point should choose a number between 4 and 10.
a result list including Lan-DeMets refined secondary boundary and the nominal significance for the secondary endpoint.
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Tamhane, A. C., Mehta, C. R., and Liu, L. (2010). Testing a primary and a secondary endpoint in a group sequential design. Biometrics 66, 1174-1184.
Tamhane, A. C., Gou, J., Jennison, C., Mehta, C. R., and Curto, T. (2017+). A gatekeeping procedure to test a primary and a secondary endpoint in a group sequential design with multiple interim looks. Biometrics, to appear.
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#require(mvtnorm) #require(ldbounds) #result <- secondaryBoundaryVecLD(alpha=0.025,tVec=c(1/2,1),primaryOBF=TRUE, # secondaryOBF=FALSE, nRepVec=c(1,1,1,1),initIntvl=c(0.8,6)) #result$secondaryBoundary #result$nomialSignificance
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