Package: Landmarking 1.0.2

Landmarking: Analysis using Landmark Models

The landmark approach allows survival predictions to be updated dynamically as new measurements from an individual are recorded. The idea is to set predefined time points, known as "landmark times", and form a model at each landmark time using only the individuals in the risk set. This package allows the longitudinal data to be modelled either using the last observation carried forward or linear mixed effects modelling. There is also the option to model competing risks, either through cause-specific Cox regression or Fine-Gray regression. To find out more about the methods in this package, please see <https://isobelbarrott.github.io/Landmarking/articles/Landmarking>.

Authors:Isobel Barrott [aut, cre], Jessica Barrett [aut], Ruth Keogh [ctb], Michael Sweeting [ctb], David Stevens [ctb]

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Landmarking.pdf |Landmarking.html✨
Landmarking/json (API)
NEWS

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

Bug tracker:https://github.com/isobelbarrott/landmarking/issues

Datasets:

On CRAN:

Conda:

5.72 score 6 stars 44 scripts 222 downloads 11 exports 108 dependencies

Last updated 2 years agofrom:8823e08b99. Checks:6 OK, 2 ERROR. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 02 2025
R-4.5-winOKMar 02 2025
R-4.5-macOKMar 02 2025
R-4.5-linuxOKMar 02 2025
R-4.4-winOKMar 02 2025
R-4.4-macOKMar 02 2025
R-4.3-winERRORMar 02 2025
R-4.3-macERRORMar 02 2025

Exports:add_cv_numberfind_LME_risk_setfind_LOCF_risk_setfit_LME_landmarkfit_LME_longitudinalfit_LOCF_landmarkfit_LOCF_longitudinalfit_survival_modelget_model_assessmentmixoutsampreturn_ids_with_LOCF

Dependencies:backportsbase64encbslibcachemcheckmatecliclustercmprskcodetoolscolorspacedata.tablediagramdigestdoParalleldplyrevaluatefansifarverfastmapfontawesomeforeachforeignFormulafsfuturefuture.applygenericsggplot2globalsgluegridExtragtablehighrHmischtmlTablehtmltoolshtmlwidgetsisobanditeratorsjquerylibjsonliteKernSmoothknitrlabelinglatticelavalifecyclelistenvmagrittrMASSMatrixMatrixModelsmemoisemetsmgcvmimemstatemultcompmunsellmvtnormnlmennetnumDerivparallellypecpillarpkgconfigplotrixpolsplineprodlimprogressrPublishquantregR6rangerrappdirsRColorBrewerRcppRcppArmadilloRcppEigenriskRegressionrlangrmarkdownrmsrpartrstudioapisandwichsassscalesshapeSparseMSQUAREMstringistringrsurvivalTH.datatibbletidyselecttimeregtinytexutf8vctrsviridisviridisLitewithrxfunyamlzoo

How to use the R package 'Landmarking'

Isobel Barrott

Rendered fromhow_to_use.Rmdusingknitr::rmarkdownon Mar 02 2025.

Last update: 2022-11-13
Started: 2021-06-05

Introduction to Landmark Models and the R package Landmarking

Rendered fromLandmarking.Rmdusingknitr::rmarkdownon Mar 02 2025.

Last update: 2022-11-13
Started: 2021-07-29