Package: CLAST 1.0.1

CLAST: Exact Confidence Limits after a Sequential Trial

The user first provides design vectors n, a and b as well as null (p0) and alternative (p1) benchmark values for the probability of success. The key function "mv.plots.SM()" calculates mean values of exact upper and lower limits based on four different rank ordering methods. These plots form the basis of selecting a rank ordering. The function "inference()" calculates exact limits from a provided realisation and ordering choice. For more information, see "Exact confidence limits after a group sequential single arm binary trial" by Lloyd, C.J. (2020), Statistics in Medicine, Volume 38, 2389-2399, <doi:10.1002/sim.8909>.

Authors:Chris J. Lloyd

CLAST_1.0.1.tar.gz
CLAST_1.0.1.zip(r-4.7)CLAST_1.0.1.zip(r-4.6)CLAST_1.0.1.zip(r-4.5)
CLAST_1.0.1.tgz(r-4.6-any)CLAST_1.0.1.tgz(r-4.5-any)
CLAST_1.0.1.tar.gz(r-4.7-any)CLAST_1.0.1.tar.gz(r-4.6-any)
CLAST_1.0.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
CLAST/json (API)
NEWS

# Install 'CLAST' in R:
install.packages('CLAST', repos = c('https://chrislloyd58.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.

1.00 score 240 downloads 21 exports 0 dependencies

Last updated from:62c869a541. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK84
source / vignettesOK139
linux-release-x86_64OK97
macos-release-arm64OK63
macos-oldrel-arm64OK75
windows-develOK105
windows-releaseOK53
windows-oldrelOK59
wasm-releaseOK83

Exports:CP.lowerCP.stats.SMCP.uppercrosserrors.SMexact.lower.limits.SMexact.upper.limits.SMinferenceJT.rank.SMLR.lowerLR.stats.SMLR.upperML.rank.SMmv.plots.SMmv.SMplt.sample.space.SMprob.SMRANKsample.spacesample.space.2sample.space.SM

Dependencies: