mixIE_MA: mixIE with model averaging

In ZhaotongL/mixIE: Mendelian randomization method with a mixture of regressions

mixIE with model averaging

Description

This is the main function of mixIE-MA

Usage

mixIE_MA(b_exp, b_out, se_exp, se_out, n, n_model = 5, ...)

Arguments

b_exp	A vector of SNP effects on the exposure variable, usually obtained from a GWAS.
b_out	A vector of SNP effects on the outcome variable, usually obtained from a GWAS.
se_exp	A vector of standard errors of b_exp.
se_out	A vector of standard errors of b_out.
n	Sample size of either one of the GWAS dataset.
n_model	Number of top models in the final candidate list, default is 5.
...	Arguments to be passed to mixIE_multiple_start

Value

A list

theta_BIC_MA

Estimated causal effect from mixIE-MA

se_BIC_MA

Estimate standard error for theta_BIC_MA

pval_BIC_MA

Two-sided p-value of theta_BIC_MA

c_BIC_MA

Estimated overdispersion parameter from mixIE-MA

r_BIC_MA

Estimated pleiotropic effect from mixIE-MA

p_BIC_MA

Estimated proportion of invalid IVs from mixIE-MA

tau_BIC_MA

A vector of (averaged) posterior probabilities of each IVs being invalid from mixIE-MA

theta_vec

A vector of estimated causal effects from n_model models

ZhaotongL/mixIE documentation built on April 14, 2023, 4:20 p.m.