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:Tianzhong Yang [aut, cre], Chunlin Li [aut], Zhichao Xu [ctb]

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Last updated 10 months agofrom:f59ed862c4. Checks:OK: 7. Indexed: yes.

Exports:CF_Rsq.measureCI.Rsq.measureRsq.measure

Dependencies:codetoolsCompQuadFormdata.tableforeachglmnetGMMATiteratorslatticeMatrixncvregRcppRcppArmadilloRcppEigenshapeSISsurvival