Package: recurrentpseudo 1.0.0

recurrentpseudo: Creates Pseudo-Observations and Analysis for Recurrent Event Data

Computation of one-, two- and three-dimensional pseudo-observations based on recurrent events and terminal events. Generalised linear models are fitted using generalised estimating equations. Technical details on the bivariate procedure can be found in "Bivariate pseudo-observations for recurrent event analysis with terminal events" (Furberg et al., 2021) <doi:10.1007/s10985-021-09533-5>.

Authors:Julie Kjærulff Furberg [aut, cre]

recurrentpseudo_1.0.0.tar.gz
recurrentpseudo_1.0.0.zip(r-4.5)recurrentpseudo_1.0.0.zip(r-4.4)recurrentpseudo_1.0.0.zip(r-4.3)
recurrentpseudo_1.0.0.tgz(r-4.4-any)recurrentpseudo_1.0.0.tgz(r-4.3-any)
recurrentpseudo_1.0.0.tar.gz(r-4.5-noble)recurrentpseudo_1.0.0.tar.gz(r-4.4-noble)
recurrentpseudo_1.0.0.tgz(r-4.4-emscripten)recurrentpseudo_1.0.0.tgz(r-4.3-emscripten)
recurrentpseudo.pdf |recurrentpseudo.html
recurrentpseudo/json (API)

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

Peer review:

Bug tracker:https://github.com/juliekfurberg/recurrentpseudo/issues

On CRAN:

3.70 score 1 stars 1 scripts 164 downloads 4 exports 45 dependencies

Last updated 2 years agofrom:c58ea803ee. Checks:OK: 3 NOTE: 4. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 01 2024
R-4.5-winNOTENov 01 2024
R-4.5-linuxNOTENov 01 2024
R-4.4-winNOTENov 01 2024
R-4.4-macNOTENov 01 2024
R-4.3-winOKNov 01 2024
R-4.3-macOKNov 01 2024

Exports:pseudo.geefitpseudo.onedimpseudo.threedimpseudo.twodim

Dependencies:backportsbroomclicodetoolscpp11data.tablediagramdigestdplyrfansifuturefuture.applygeepackgenericsglobalsglueKernSmoothlatticelavalifecyclelistenvmagrittrMASSMatrixnumDerivparallellypillarpkgconfigprodlimprogressrpurrrR6RcpprlangshapeSQUAREMstringistringrsurvivaltibbletidyrtidyselectutf8vctrswithr

recurrentpseudo: An R package for analysing recurrent events in the presence of terminal events using pseudo-observations

Rendered fromrecurrentpseudo.Rmdusingknitr::rmarkdownon Nov 01 2024.

Last update: 2023-03-22
Started: 2022-05-09