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RsqMed  

Total Mediation Effect Size Measure for High-Dimensional Mediators
View on CRAN: Click here


Download and install RsqMed package within the R console
Install from CRAN:
install.packages("RsqMed")

Install from Github:
library("remotes")
install_github("cran/RsqMed")

Install by package version:
library("remotes")
install_version("RsqMed", "1.1")



Attach the package and use:
library("RsqMed")
Maintained by
Tianzhong Yang
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-02-02
Latest Update: 2023-11-14
Description:
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" . 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" .
How to cite:
Tianzhong Yang (2020). RsqMed: Total Mediation Effect Size Measure for High-Dimensional Mediators. R package version 1.1, https://cran.r-project.org/web/packages/RsqMed. Accessed 03 Dec. 2024.
Previous versions and publish date:
0.1.7.1 (2020-02-02 17:00), 0.2.1.0 (2022-11-07 21:40)
Other packages that cited RsqMed R package
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Other R packages that RsqMed depends, imports, suggests or enhances
Complete documentation for RsqMed
Functions, R codes and Examples using the RsqMed R package
Some associated functions: CF_Rsq.measure . CI.Rsq.measure . Rsq.measure . example . 
Some associated R codes: CrossFittedR2.R . RsqMed.R . RsqMed_sd.R .  Full RsqMed package functions and examples
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