Package: prome 4.0.2.5

Bin Wang

prome: Patient-Reported Outcome Data Analysis with Stan

Estimation for blinding bias in randomized controlled trials with a latent continuous outcome, a binary response depending on treatment and the latent outcome, and a noisy surrogate subject to possibly response-dependent measurement error. Implements EM estimators in R backed by compiled C routines for models with and without the restriction delta0 = 0, and Bayesian Stan wrappers for the same two models. Functions were added for latent outcome models with differential measurement error.

Authors:Bin Wang [aut, cre]

prome_4.0.2.5.tar.gz
prome_4.0.2.5.tar.gz(r-4.7-arm64)prome_4.0.2.5.tar.gz(r-4.7-x86_64)prome_4.0.2.5.tar.gz(r-4.6-arm64)prome_4.0.2.5.tar.gz(r-4.6-x86_64)
prome_4.0.2.5.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
prome/json (API)

# Install 'prome' in R:
install.packages('prome', 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.

1.78 score 506 downloads 1 exports 55 dependencies

Last updated from:b1501afbb3. Checks:6 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK214
linux-devel-x86_64OK219
source / vignettesOK196
linux-release-arm64OK248
linux-release-x86_64OK214
wasm-releaseOK135

Exports:blinding.test

Dependencies:abindbackportsBHBIbridgesamplingBrobdingnagcallrcheckmateclicodacpp11descdistributionalfarvergenericsggplot2gluegridExtragtableinlineisobandlabelinglatticelifecycleloomagrittrMatrixmatrixStatsmvtnormnumDerivpillarpkgbuildpkgconfigposteriorprocessxpsQuickJSRR6RColorBrewerRcppRcppEigenRcppParallelrlangrstanS7scalesStanHeadersstringistringrtensorAtibbleutf8vctrsviridisLitewithr

Readme and manuals

Help Manual

Help pageTopics
Unblinding bias correctionblinding.test test.stan