Package: ASSISTant 1.4.3

Balasubramanian Narasimhan

ASSISTant: Adaptive Subgroup Selection in Group Sequential Trials

Clinical trial design for subgroup selection in three-stage group sequential trial. Includes facilities for design, exploration and analysis of such trials. An implementation of the initial DEFUSE-3 trial is also provided as a vignette.

Authors:Tze Leung Lai [ctb], Philip Lavori [aut], Olivia Liao [aut], Balasubramanian Narasimhan [aut, cre], Ka Wai Tsang [aut]

ASSISTant_1.4.3.tar.gz
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ASSISTant.pdf |ASSISTant.html✨
ASSISTant/json (API)
NEWS

# Install 'ASSISTant' in R:
install.packages('ASSISTant', repos = c('https://bnaras.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/bnaras/assistant/issues

Datasets:
  • LLL.SETTINGS - Design and trial settings used in the Lai, Lavori, Liao paper simulations

On CRAN:

4.54 score 23 scripts 331 downloads 15 exports 22 dependencies

Last updated 5 years agofrom:b6598c72ff. Checks:OK: 1 ERROR: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 19 2024
R-4.5-winERRORNov 19 2024
R-4.5-linuxERRORNov 19 2024
R-4.4-winERRORNov 19 2024
R-4.4-macERRORNov 19 2024
R-4.3-winERRORNov 19 2024
R-4.3-macERRORNov 19 2024

Exports:ASSISTDesignASSISTDesignBASSISTDesignCcolNamesForStagecomputeMeanAndSDcomputeMHPBoundariescomputeMHPBoundaryITTDEFUSE3DesigngenerateDiscreteDatagenerateNormalDatagroupSampleSizemHP.bmHP.btildemHP.cwilcoxon

Dependencies:clidplyrevaluatefansigenericsgluehighrknitrlifecyclemagrittrmvtnormpillarpkgconfigR6rlangtibbletidyselectutf8vctrswithrxfunyaml

Adaptive Subgroup Selection in Sequential Trials

Tze Leung Lai, Philip W. Lavori, Olivia Liao, Ka Wai Tsang and Balasubramanian Narasimhan

Rendered fromASSISTant.Rmdusingknitr::rmarkdownon Nov 19 2024.

Last update: 2019-11-22
Started: 2016-05-02

Design of the DEFUSE3 Trial

Tze Leung Lai, Philip W. Lavori, Olivia Liao, Ka Wai Tsang and Balasubramanian Narasimhan

Rendered fromdefuse3.Rmdusingknitr::rmarkdownon Nov 19 2024.

Last update: 2019-11-22
Started: 2016-05-02

Using Discrete Rankin Scores

Tze Leung Lai, Philip W. Lavori, Olivia Liao, Ka Wai Tsang and Balasubramanian Narasimhan

Rendered fromRankin.Rmdusingknitr::rmarkdownon Nov 19 2024.

Last update: 2019-11-22
Started: 2017-06-30

Readme and manuals

Help Manual

Help pageTopics
Three stage group sequential adaptive design with subgroup selectionASSISTant-package ASSISTant
A class to encapsulate the adaptive clinical trial design of Lai, Lavori and LiaoASSISTDesign
A fixed sample design to compare against the adaptive clinical trial design of Lai, Lavori and Liao.ASSISTDesignB
A fixed sample RCT design to compare against the adaptive clinical trial design of Lai, Lavori and Liao.ASSISTDesignC
Return a vector of column names for statistics for a given stagecolNamesForStage
Compute the mean and sd of a discrete Rankin distributioncomputeMeanAndSD
Compute the three modified Haybittle-Peto boundariescomputeMHPBoundaries
Compute the three modified Haybittle-Peto boundaries and effect sizecomputeMHPBoundaryITT
The DEFUSE3 designDEFUSE3Design
A data generation function using a discrete distribution for Rankin score rather than a normal distributiongenerateDiscreteData
A data generation function along the lines of what was used in the Lai, Lavori, Liao paper. score rather than a normal distributiongenerateNormalData
Compute the sample size for any group at a stage assuming a nested structure as in the paper.groupSampleSize
Design and trial settings used in the Lai, Lavori, Liao paper simulationsLLL.SETTINGS
Compute the efficacy boundary (modified Haybittle-Peto) for the first two stagesmHP.b
Compute the futility boundary (modified Haybittle-Peto) for the first two stagesmHP.btilde
Compute the efficacy boundary (modified Haybittle-Peto) for the final (third) stagemHP.c
Compute the standardized Wilcoxon test statistic for two sampleswilcoxon