compound.Cox: Univariate Feature Selection and Compound Covariate for Predicting 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) <DOI:10.3390/biomedicines11030797>.

Package details

AuthorTakeshi Emura, Hsuan-Yu Chen, Shigeyuki Matsui, Yi-Hau Chen
MaintainerTakeshi Emura <takeshiemura@gmail.com>
LicenseGPL-2
Version3.30
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("compound.Cox")

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compound.Cox documentation built on July 26, 2023, 5:39 p.m.