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An implementation of calculating the R-squared measure as a total mediation effect size measure and its confidence interval for moderate- or high-dimensional mediator models. It gives an option to filter out non-mediators using variable selection methods. The original R package is directly related to the paper Yang et al (2021) "Estimation of mediation effect for high-dimensional omics mediators with application to the Framingham Heart Study" <doi:10.1101/774877>. The new version contains a choice of using cross-fitting, which is computationally faster. The details of the cross-fitting method are available in the paper Xu et al (2023) "Speeding up interval estimation for R2-based mediation effect of high-dimensional mediators via cross-fitting" <doi:10.1101/2023.02.06.527391>.
| Version: | 1.1 |
| Depends: | R (≥ 3.5.0) |
| Imports: | SIS (≥ 0.8), GMMAT (≥ 1.4.1) |
| Published: | 2023-11-14 |
| DOI: | 10.32614/CRAN.package.RsqMed |
| Author: | Tianzhong Yang [aut, cre], Chunlin Li [aut], Zhichao Xu [ctb] |
| Maintainer: | Tianzhong Yang <yang3704 at umn.edu> |
| License: | GPL-3 |
| NeedsCompilation: | no |
| CRAN checks: | RsqMed results |
| Reference manual: | RsqMed.pdf |
| Package source: | RsqMed_1.1.tar.gz |
| Windows binaries: | r-devel: RsqMed_1.1.zip, r-release: RsqMed_1.1.zip, r-oldrel: RsqMed_1.1.zip |
| macOS binaries: | r-release (arm64): RsqMed_1.1.tgz, r-oldrel (arm64): RsqMed_1.1.tgz, r-release (x86_64): RsqMed_1.1.tgz, r-oldrel (x86_64): RsqMed_1.1.tgz |
| Old sources: | RsqMed archive |
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