Total Mediation Effect Size Measure for High-Dimensional Mediators


[Up] [Top]

Documentation for package ‘RsqMed’ version 1.1

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).