Package: PwrGSD 2.3.8

PwrGSD: Power in a Group Sequential Design

Tools for the evaluation of interim analysis plans for sequentially monitored trials on a survival endpoint; tools to construct efficacy and futility boundaries, for deriving power of a sequential design at a specified alternative, template for evaluating the performance of candidate plans at a set of time varying alternatives. See Izmirlian, G. (2014) <doi:10.4310/SII.2014.v7.n1.a4>.

Authors:Grant Izmirlian [aut, cre]

PwrGSD_2.3.8.tar.gz
PwrGSD_2.3.8.zip(r-4.7-x86_64)PwrGSD_2.3.8.zip(r-4.7-arm64)PwrGSD_2.3.8.zip(r-4.6-x86_64)PwrGSD_2.3.8.zip(r-4.6-arm64)PwrGSD_2.3.8.zip(r-4.5-x86_64)
PwrGSD_2.3.8.tgz(r-4.6-x86_64)PwrGSD_2.3.8.tgz(r-4.6-arm64)PwrGSD_2.3.8.tgz(r-4.5-x86_64)PwrGSD_2.3.8.tgz(r-4.5-arm64)
PwrGSD_2.3.8.tar.gz(r-4.7-arm64)PwrGSD_2.3.8.tar.gz(r-4.7-x86_64)PwrGSD_2.3.8.tar.gz(r-4.6-arm64)PwrGSD_2.3.8.tar.gz(r-4.6-x86_64)
PwrGSD_2.3.8.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
PwrGSD/json (API)

# Install 'PwrGSD' in R:
install.packages('PwrGSD', repos = c('https://izmirlig.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:
  • lung - Mayo Clinic Lung Cancer Data

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

4.04 score 2 packages 61 scripts 476 downloads 30 exports 3 dependencies

Last updated from:b9a00976c5. Checks:15 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK97
linux-devel-x86_64OK110
source / vignettesOK186
linux-release-arm64OK95
linux-release-x86_64OK113
macos-release-arm64OK174
macos-release-x86_64OK337
macos-oldrel-arm64OK127
macos-oldrel-x86_64OK449
windows-devel-arm64OK332
windows-devel-x86_64OK156
windows-release-arm64OK352
windows-release-x86_64OK115
windows-oldrel-x86_64OK102
wasm-releaseOK87

Exports:agghazas.boundariesCDFOR2LRRCondPowercpd.PwrGSDCRRtoRRCY2TOShazdetailDXElementsEX1gXKGrpSeqBndsgsd.densHaybittleIntSurvDiffLanDemetslookupmystackmysurvfitObrienFlemingPocockPowPowerPwrGSDRCM2RRRR2RCMSCSCtoBdrySimGSBwtdlogrank

Dependencies:latticeMatrixsurvival

Using cpd-PwrGSD
Introduction
Rendered fromcpd-PwrGSD-vignette.Rnwusingutils::Sweave

Last update: 2019-04-15
Started: 2014-03-14

Using GrpSeqBnds
Introduction
Rendered fromGrpSeqBnds-vignette.Rnwusingutils::Sweave

Last update: 2019-04-15
Started: 2014-03-14

Using PwrGSD
Introduction
Rendered fromPwrGSD-vignette.Rnwusingutils::Sweave

Last update: 2019-04-15
Started: 2014-03-14

Readme and manuals

Help Manual

Help pageTopics
Aggregated Hazardagghaz
Convert a "PwrGSD" object to a "boundaries" objectas.boundaries
Convert CDF Odds Ratio to Logged Relative RisksCDFOR2LRR
Conditional type I and type II error probabilities given current value of the test statisticCondPower
Create a skeleton compound PwrGSD objectcpd.PwrGSD
Cumulative-risk ratios to risk ratiosCRRtoRR
Calender year rates to Study Year RatesCY2TOShaz
Function to extract the 'detail' component from a 'PwrGSD' objectdetail
A utility function for forming differencesDX
Create a subset of a "cpd.PwrGSD" objectElements
A function for computing the bias adjusted point estimate for a statistic observed to cross the efficacy boundary.EX1gXK
Computes efficacy and futility boundariesGrpSeqBnds
A function for computing the probability density for the group sequentially monitored test statistic.gsd.dens
The Haybittle method of Boundary ConstructionHaybittle
Weighted Integrated Survival function testIntSurvDiff
The Lan-Demets method of Boundary ConstructionLanDemets
Lookup values for a piecewise constant functionlookup
Mayo Clinic Lung Cancer Datalung
Stack a datasetmystack
My Survfitmysurvfit
The O'Brien-Fleming Alpha Spending FunctionObrienFleming
Plot Method for cpd.PwrGSD objectsplot.cpd.PwrGSD
The Pocock Alpha Spending FunctionPocock
The Wang-Tsiatis Power Alpha Spending FunctionPow
Extract the Power resultsPower
Calculate Power in a Group Sequential DesignPwrGSD
Relative cumulative mortality to Relative RiskRCM2RR
Relative risk to Relative Cumulative MortalityRR2RCM
The Stochastic Curtailment method of Boundary ConstructionSC
Converts a stochastic curtailment boundary (conditional type I or II error probability) into a (efficacy or futility) boundary on the standardized Z scaleSCtoBdry
Verifies the results of "GrpSeqBnds" via simulationSimGSB
Weighted log-rank testwtdlogrank