Univariate Feature Selection and Compound Covariate for Predicting Survival, Including Copula-Based Analyses for Dependent Censoring R package compound.Cox version 3.33 CRAN Task View: Survival (https://CRAN.R-project.org/view=Survival) Univariate feature selection and compound covariate methods under the Cox model with high-dimensional features (e.g., gene expressions). Available are survival data for non-small-cell lung cancer patients with gene expressions (Chen et al 2007 New Engl J Med) <DOI:10.1056/NEJMoa060096>, statistical methods in Emura et al (2012 PLoS ONE) <DOI:10.1371/journal.pone.0047627>, Emura & Chen (2016 Stat Methods Med Res) <DOI:10.1177/0962280214533378>, and Emura et al (2019)<DOI:10.1016/j.cmpb.2018.10.020>. Algorithms for generating correlated gene expressions are also available. Estimation of survival functions via copula-graphic (CG) estimators is also implemented, which is useful for sensitivity analyses under dependent censoring (Yeh et al 2023 Biomedicines) <DOI:10.3390/biomedicines11030797> and factorial survival analyses (Emura et al 2024 Stat Methods Med Res) <DOI:10.1177/09622802231215805>. Software Depends: numDeriv, survival, MASS Takeshi Emura <takeshiemura@gmail.com> Comprehensive R Archive Network (CRAN) Takeshi Emura [aut, cre], Hsuan-Yu Chen [aut], Shigeyuki Matsui [aut], Yi-Hau Chen [aut] GPL-2 2025-06-16 application/tgz https://CRAN.R-project.org/package=compound.Cox doi:10.32614/CRAN.package.compound.Cox