RsqMed: Total Mediation Effect Size Measure for High-Dimensional
Mediators
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 |
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