compound.Cox
Univariate Feature Selection and Compound Covariate for Predicting Survival, Including Copula-Based Analyses for Dependent Censoring
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.
- Version3.32
- R versionunknown
- LicenseGPL-2
- Needs compilation?No
- Last release01/11/2025
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Team
Takeshi Emura
MaintainerShow author detailsHsuan-Yu Chen
Show author detailsRolesAuthorYi-Hau Chen
Show author detailsRolesAuthorShigeyuki Matsui
Show author detailsRolesAuthor
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