This software package provides Cox survival analysis for high-dimensional and multiblock datasets. It encompasses a suite of functions dedicated from the classical Cox regression to newest analysis, including Cox proportional hazards model, Stepwise Cox regression, and Elastic-Net Cox regression, Sparse Partial Least Squares Cox regression (sPLS-COX) incorporating three distinct strategies, and two Multiblock-PLS Cox regression (MB-sPLS-COX) methods. This tool is designed to adeptly handle high-dimensional data, and provides tools for cross-validation, plot generation, and additional resources for interpreting results. While references are available within the corresponding functions, key literature is mentioned below. Terry M Therneau (2024) <https://CRAN.R-project.org/package=survival>, Noah Simon et al. (2011) <doi:10.18637/jss.v039.i05>, Philippe Bastien et al. (2005) <doi:10.1016/j.csda.2004.02.005>, Philippe Bastien (2008) <doi:10.1016/j.chemolab.2007.09.009>, Philippe Bastien et al. (2014) <doi:10.1093/bioinformatics/btu660>, Kassu Mehari Beyene and Anouar El Ghouch (2020) <doi:10.1002/sim.8671>, Florian Rohart et al. (2017) <doi:10.1371/journal.pcbi.1005752>.
Version: 1.1.3 Depends: R (≥ 4.1.0) Imports: caret, cowplot, furrr, future, ggrepel, ggplot2, ggpubr, glmnet, MASS, mixOmics, methods, patchwork, progress, purrr, Rdpack, scattermore, stats, survcomp, survival, survminer, svglite, tidyr, utils Suggests: ggforce, grDevices, knitr, nsROC, RColorConesa, risksetROC, rmarkdown, smoothROCtime, survivalROC Published: 2025-06-02 DOI: 10.32614/CRAN.package.Coxmos Author: Pedro Salguero GarcÃa [aut, cre, rev], Sonia Tarazona Campos [ths], Ana Conesa Cegarra [ths], Kassu Mehari Beyene [ctb], Luis Meira Machado [ctb], Marta Sestelo [ctb], Artur Araújo [ctb] Maintainer: Pedro Salguero GarcÃa <pedrosalguerog at gmail.com> BugReports: https://github.com/BiostatOmics/Coxmos/issues License: CC BY 4.0 URL: https://github.com/BiostatOmics/Coxmos NeedsCompilation: yes Materials: README CRAN checks: Coxmos results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=Coxmos to link to this page.
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