Adaptive Subgroup Selection in Group Sequential Trials

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Documentation for package ‘ASSISTant’ version 1.4.3

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

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ASSISTant	Three stage group sequential adaptive design with subgroup selection
ASSISTDesign	A class to encapsulate the adaptive clinical trial design of Lai, Lavori and Liao
ASSISTDesignB	A fixed sample design to compare against the adaptive clinical trial design
ASSISTDesignC	A fixed sample RCT design to compare against the adaptive clinical trial design of Lai, Lavori and Liao.
colNamesForStage	Return a vector of column names for statistics for a given stage
computeMeanAndSD	Compute the mean and sd of a discrete Rankin distribution
computeMHPBoundaries	Compute the three modified Haybittle-Peto boundaries
computeMHPBoundaryITT	Compute the three modified Haybittle-Peto boundaries and effect size
conformParameters	Conform designParameters so that weights are turned in to probabilities, the null and control distributions are proper matrices etc.
DEFUSE3Design	The DEFUSE3 design
generateDiscreteData	A data generation function using a discrete distribution for Rankin score rather than a normal distribution
generateNormalData	A data generation function along the lines of what was used in the Lai, Lavori, Liao paper. score rather than a normal distribution
groupSampleSize	Compute the sample size for any group at a stage assuming a nested structure as in the paper.
LLL.SETTINGS	Design and trial settings used in the Lai, Lavori, Liao paper simulations
mHP.b	Compute the efficacy boundary (modified Haybittle-Peto) for the first two stages
mHP.btilde	Compute the futility boundary (modified Haybittle-Peto) for the first two stages
mHP.c	Compute the efficacy boundary (modified Haybittle-Peto) for the final (third) stage
wilcoxon	Compute the standardized Wilcoxon test statistic for two samples