mrMed: a function to perform the MR-based mediation analysis using...

In scllin/toypack:

a function to perform the MR-based mediation analysis using summary statistics from genome-wide association studies (GWAS)

Description

mrMed includes several methods to perform MR-based mediation analysis and provides corresponding estimates of the total effect (TE), direct effect (DE), indirect effect (IE), and mediation proportion (rho).

Usage

    mrMed(dat_mrMed, method_list=c("Diff_IVW","Prod_IVW","Prod_Median"))

Arguments

dat_mrMed	dataframe, the required format are refered to the examples
method_list	vector of characters, name(s) of the MR-based mediation methods

Value

TE	Results for the total effect including point estimate (b), standard error of the estimate (se), p-value (pval), and the upper bound and lower bound of 95% confidence interval.
DE	Results for the direct effect including point estimate (b), standard error of the estimate (se), p-value (pval), and the upper bound and lower bound of 95% confidence interval.
IE	Results for the indirect effect including point estimate (b), standard error of the estimate (se), p-value (pval), and the upper bound and lower bound of 95% confidence interval.
rho	Results for the mediation proportion including point estimate (b), standard error of the estimate (se), p-value (pval), and the upper bound and lower bound of 95% confidence interval.

Author(s)

Shu-Chin Lin

References

Causal Mediation Analysis: A Summary-Data Mendelian Randomization Approach

Examples

data(WHR_T2D_CAD)
mrMed(dat_mrMed=WHR_T2D_CAD, method_list=c("Diff_IVW","Prod_IVW","Prod_Median"))

scllin/toypack documentation built on June 3, 2022, 10:36 p.m.