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>.
Version: 1.0.0 Depends: R (≥ 2.10) Imports: nlme, riskRegression, dplyr, pec, methods, prodlim, stats, survival, mstate, ggplot2 Suggests: testthat (≥ 3.0.0), knitr, rmarkdown, JM Published: 2022-02-15 DOI: 10.32614/CRAN.package.Landmarking Author: Isobel Barrott [aut, cre], Jessica Barrett [aut], Ruth Keogh [ctb], Michael Sweeting [ctb], David Stevens [ctb] Maintainer: Isobel Barrott <isobel.barrott at gmail.com> BugReports: https://github.com/isobelbarrott/Landmarking/issues License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] URL: https://github.com/isobelbarrott/Landmarking/ NeedsCompilation: no Materials: README, NEWS CRAN checks: Landmarking results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=Landmarking to link to this page.
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