R: Total Mediation Effect Size Measure for High-Dimensional Mediators

# Total Mediation Effect Size Measure for High-Dimensional Mediators

## Documentation for package ‘RsqMed’ version 1.1

- DESCRIPTION file

## Help Pages

CF_Rsq.measure | Function to calculate the Rsq function as a total effect size measure for mediation effect using cross-fitted estimation
CI.Rsq.measure | Functions to generate the confidence interval of the Rsq measure using nonparametric bootstrap.
example | Example dataset
Rsq.measure | Function to calculate the Rsq function as a total mediation effect size measure (Gaussian outcome only). If method = 'iSIS', a two-step procedure is performed, where the first step filters the non-mediators based on the first p proportion of the data and the second step calculates the point estimates for Rsq using random-effect models on the remaining data. If method = 'ALL', Rsq is calculated based on all subjects and mediators (assuming all mediators are the true mediators). It is optional to adding filtering step on putative mediators to exclude M1 type of non-mediators (See Yang et al, BMC bioinformatics, 2021).