Package: gsMeanFreq 0.1.0

Qinghua Lian

gsMeanFreq: Group Sequential Clinical Trial Designs for Composite Endpoints

Simulating composite endpoints with recurrent and terminal events under staggered entry, and for constructing one- and two-sample group sequential test statistics and monitoring boundaries based on the mean frequency function. Details will be available in an upcoming publication.

Authors:Qinghua Lian [aut, cre], Kwang Woo Ahn [ctb], Soyoung Kim [ctb], Michael J Martens [aut], Brent R. Logan [ctb]

gsMeanFreq_0.1.0.tar.gz
gsMeanFreq_0.1.0.tar.gz(r-4.7-any)gsMeanFreq_0.1.0.tar.gz(r-4.6-any)
gsMeanFreq_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
gsMeanFreq/json (API)

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

On CRAN:

Conda:

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

1.70 score 160 downloads 23 exports 76 dependencies

Last updated from:6b55e40e49. Checks:4 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK147
source / vignettesOK201
linux-release-x86_64OK156
wasm-releaseOK122

Exports:Apply.calendar.censoringApply.calendar.censoring.2find.beta.trtfind.cfind.Delta.given.powerfind.lambda_0.given.Deltafind.lambda_0.given.mu0OBFOneSample.Estimator.sequentialOnesample.generate.sequentialSolve.beta.given.powerTrue.muTwoSample.Boundary.TTFETwoSample.Constant.GTTwoSample.Constant.LRTwoSample.Estimator.GT.sequentialTwoSample.Estimator.LR.sequentialTwoSample.Estimator.TTFE.sequentialTwoSample.generate.sequentialTwoSample.Q.Cov.Estimator.Sequential.GTTwoSample.Q.Cov.Estimator.Sequential.LRTwoSample.Wald.and.BoundaryTwoSample.Z.Var.Estimator.Sequential.TTFE

Dependencies:base64encbdsmatrixbigDbitopsbslibcachemclicodetoolscommonmarkcpp11curldigestdplyrevaluatefarverfastmapfontawesomeforeachfsgenericsggplot2gluegsDesigngtgtablehighrhtmltoolshtmlwidgetsisobanditeratorsjquerylibjsonlitejuicyjuiceknitrlabelinglatticelifecyclelitedownmagrittrmarkdownMatrixmemoisemimemvtnormpillarpkgconfigpracmapurrrr2rtfR6rappdirsRColorBrewerRcppreactablereactRrlangrmarkdownS7sassscalesstringistringrsurvivaltibbletidyrtidyselecttinytexutf8V8vctrsviridisLitewithrxfunxml2xtableyaml

Readme and manuals

Help Manual

Help pageTopics
Function to apply a given calendar time as effective censoring time.Apply.calendar.censoring
Function to apply a given calendar time as effective censoring time for two-sample composite endpoint data.Apply.calendar.censoring.2
Function to solve for treatment effect size given target power for two-sample tests.find.beta.trt
Function to solve for a group sequential critical value at a given stagefind.c
Function to solve for the mean frequency effect size given target power for one-sample simulations.find.Delta.given.power
Function to solve for the baseline recurrent event rate given a mean frequency difference for one-sample simulations.find.lambda_0.given.Delta
Function to solve for the baseline recurrent event rate given a target mean frequency for one-sample simulations.find.lambda_0.given.mu0
O'Brien-Flemming error spending function.OBF
Function to estimate the one-sample mean frequency under a group sequential design.OneSample.Estimator.sequential
Function to simulate one-sample composite endpoint data under staggered entry.Onesample.generate.sequential
Function to solve for the treatment effect parameter to achieve target power by Monte Carlo simulation.Solve.beta.given.power
Function to calculate the true value of the mean frequency function.True.mu
Function to calculate the sequential rejection boundaries for the time-to-first-event (TTFE) method.TwoSample.Boundary.TTFE
Function to compute calibration constants for the two-sample generalized-t statistics.TwoSample.Constant.GT
Function to compute calibration constants for the two-sample generalized log-rank statistics.TwoSample.Constant.LR
Function to calculate the two-sample generalized-t statistic for composite endpoint under sequential monitoring.TwoSample.Estimator.GT.sequential
Function to calculate the two-sample generalized log-rank statistic for composite endpoint under sequential monitoring.TwoSample.Estimator.LR.sequential
Function to calculate the Z statistics and variance for the time-to-first-event (TTFE) method.TwoSample.Estimator.TTFE.sequential
Function to simulate two-sample composite endpoint data under staggered entry.TwoSample.generate.sequential
Function to calculate stage-wise test statistics, variances, and correlation for two-sample generalized-t statistics.TwoSample.Q.Cov.Estimator.Sequential.GT
Function to calculate stage-wise test statistics, variances, and correlation for two-sample generalized log-rank statistics.TwoSample.Q.Cov.Estimator.Sequential.LR
Function to calculate the Wald statistics and group sequential boundaries for two-sample monitoring.TwoSample.Wald.and.Boundary
Function to calculate the two-sample time-to-first-event (TTFE) statistics and variances across multiple calendar times.TwoSample.Z.Var.Estimator.Sequential.TTFE