Package: accrual 1.4

Junhao Liu

accrual: Bayesian Accrual Prediction

Participant recruitment for medical research is challenging. Slow accrual leads to delays in research. Accrual monitoring during the process of recruitment is critical. Researchers need reliable tools to manage the accrual rate. We developed a Bayesian method that integrates the researcher's experience with previous trials and data from the current study, providing reliable predictions on accrual rate for clinical studies. For more details and background on these methodologies, see the publications of Byron, Stephen and Susan (2008) <doi:10.1002/sim.3128>, and Yu et al. (2015) <doi:10.1002/sim.6359>. In this R package, Bayesian accrual prediction functions are presented, which can be easily used by statisticians and clinical researchers.

Authors:Junhao Liu [aut, cre], Yu Jiang [aut], Cen Wu [aut], Steve Simon [aut], Matthew S. Mayo [aut], Rama Raghavan [aut], Byron J. Gajewski [aut]

accrual_1.4.tar.gz
accrual_1.4.tar.gz(r-4.5-noble)accrual_1.4.tar.gz(r-4.4-noble)
accrual_1.4.tgz(r-4.4-emscripten)accrual_1.4.tgz(r-4.3-emscripten)
accrual.pdf |accrual.html
accrual/json (API)

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

Peer review:

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

1.08 score 1 stars 12 scripts 380 downloads 11 exports 9 dependencies

Last updated 1 years agofrom:a86aba9b03. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKDec 21 2024
R-4.5-linuxOKDec 21 2024

Exports:accrual.dataaccrual.guiaccrual.multi.naccrual.n.hedgingaccrual.n.informaccrual.n.plotaccrual.plot.multicenteraccrual.plotsaccrual.T.hedgingaccrual.T.informaccrual.T.plot

Dependencies:ellipsefguilatticeMASSMatrixnlmeSMPracticalssurvivaltcltk2