A subgroup identification method for precision medicine based on quantitative objectives. This method can handle continuous, binary and survival endpoint for both prognostic and predictive case. For the predictive case, the method aims at identifying a subgroup for which treatment is better than control by at least a pre-specified or auto-selected constant. For the prognostic case, the method aims at identifying a subgroup that is at least better than a pre-specified/auto-selected constant. The derived signature is a linear combination of predictors, and the selected subgroup are subjects with the signature > 0. The false discover rate when no true subgroup exists is controlled at a user-specified level.
Version: 1.1.7 Imports: stats (≥ 3.4.3), graphics (≥ 3.4.3), utils (≥ 3.4.3), glmnet (≥ 2.0-13), survival (≥ 2.41-3), ggplot2 (≥ 2.2.1), methods (≥ 3.4.3) Published: 2024-08-19 DOI: 10.32614/CRAN.package.squant Author: YAN SUN [aut, cre, cph], LING CHENG [aut], A.S. HEDAYAT [aut] Maintainer: YAN SUN <sunyanrobin at gmail.com> License: GPL-3 NeedsCompilation: no Citation: squant citation info CRAN checks: squant results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=squant to link to this page.
RetroSearch is an open source project built by @garambo | Open a GitHub Issue
Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo
HTML:
3.2
| Encoding:
UTF-8
| Version:
0.7.4