Time-to-Event Landmark Analysis using an Array of Longitudinal and Survival Sub-Models R package landmaRk version 0.1.3 Provides a modular end-to-end framework for dynamic risk prediction based on time-to-event and longitudinal data. This allows flexible specifications for the longitudinal and survival sub-models. The 'landmaRk' package enables reproducible benchmarks of different model choices, including cross-validation to assess out-of-sample predictive performance. Methods are described in Velasco-Pardo, Constantine-Cooke, Lees and Vallejos (2026, manuscript under preparation) 'Landmarking with Latent Class Mixed Models for Dynamic Prediction of Time-to-event Data with Heterogeneous Biomarker Trajectories'. Software Depends: R (>= 4.1.0), survival Imports: dplyr, ggplot2, lme4, Matrix, methods, pec, riskRegression, rlang, lcmm (>= 2.2.2), doParallel, foreach, utils, prodlim Suggests: JMbayes2, knitr, rmarkdown, testthat (>= 3.0.0), xml2, tidyverse, spelling, joineR, survminer, withr Victor Velasco-Pardo <vvelasco@ed.ac.uk> Comprehensive R Archive Network (CRAN) Victor Velasco-Pardo [aut, cre] (ORCID: <https://orcid.org/0000-0002-7166-1573>), Nathan Constantine-Cooke [aut] (ORCID: <https://orcid.org/0000-0002-4437-8713>), Charlie Lees [aut] (ORCID: <https://orcid.org/0000-0002-0732-8215>), Catalina Vallejos [aut] (ORCID: <https://orcid.org/0000-0003-3638-1960>) GPL (>= 3) 2026-07-02 application/tgz https://CRAN.R-project.org/package=landmaRk doi:10.32614/CRAN.package.landmaRk en-GB