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precmed: Precision Medicine
A doubly robust precision medicine approach to fit, cross-validate and visualize prediction models for the conditional average treatment effect (CATE). It implements doubly robust estimation and semiparametric modeling approach of treatment-covariate interactions as proposed by Yadlowsky et al. (2020) <doi:10.1080/01621459.2020.1772080>.
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Package details |
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| Author | Lu Tian [aut] (<https://orcid.org/0000-0002-5893-0169>), Xiaotong Jiang [aut] (<https://orcid.org/0000-0003-3698-4526>), Gabrielle Simoneau [aut] (<https://orcid.org/0000-0001-9310-6274>), Biogen MA Inc. [cph], Thomas Debray [ctb, cre] (<https://orcid.org/0000-0002-1790-2719>), Stan Wijn [ctb] (<https://orcid.org/0000-0003-3782-6677>), Joana Caldas [ctb] |
| Maintainer | Thomas Debray <tdebray@fromdatatowisdom.com> |
| License | Apache License (== 2.0) |
| Version | 1.1.0 |
| URL | https://github.com/smartdata-analysis-and-statistics/precmed https://smartdata-analysis-and-statistics.github.io/precmed/ |
| Package repository | View on CRAN |
| Installation |
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