Package: RsqMed 1.1
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>.
Authors:
RsqMed_1.1.tar.gz
RsqMed_1.1.zip(r-4.7-any)RsqMed_1.1.zip(r-4.6-any)RsqMed_1.1.zip(r-4.5-any)
RsqMed_1.1.tgz(r-4.6-any)RsqMed_1.1.tgz(r-4.5-any)
RsqMed_1.1.tar.gz(r-4.7-any)RsqMed_1.1.tar.gz(r-4.6-any)
RsqMed_1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
RsqMed/json (API)
| # Install 'RsqMed' in R: |
| install.packages('RsqMed', repos = c('https://ytzhong.r-universe.dev', 'https://cloud.r-project.org')) |
- example - Example dataset
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:f59ed862c4. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel | OK | 118 | ||
| source / vignettes | OK | 212 | ||
| linux-release | OK | 142 | ||
| macos-release | OK | 165 | ||
| macos-oldrel | OK | 160 | ||
| windows-devel | OK | 58 | ||
| windows-release | OK | 61 | ||
| windows-oldrel | OK | 65 | ||
| wasm-release | OK | 108 |
Exports:CF_Rsq.measureCI.Rsq.measureRsq.measure
Dependencies:codetoolsCompQuadFormdata.tabledoParallelforeachgcdnetglmnetGMMATiteratorslatticeMatrixmsaenetmvtnormncvregnnetRcppRcppArmadilloRcppEigenshapeSISsurvival