MVmr_cML_DP function

MVMRcML method with Data Perturbation

This is the internal MVMRcML-DP function of mr_mvcML.

MVmr_cML_DP(
  b_exp,
  b_out,
  se_bx,
  Sig_inv_l,
  n,
  K_vec = as.numeric(c()),
  random_start = 1L,
  num_pert = 100L,
  min_theta_range = -0.5,
  max_theta_range = 0.5,
  maxit = 100L,
  thres = 1e-04
)

Arguments

• b_exp: A m*L matrix of SNP effects on the exposure variable.
• b_out: A m*1 matrix of SNP effects on the outcome variable.
• se_bx: A m*L matrix of standard errors of b_exp.
• Sig_inv_l: A list of the inverse of m covariance matrices.
• n: The smallest sample size of the L+1 GWAS dataset.
• K_vec: Sets of candidate K's, the constraint parameter representing number of invalid IVs.
• random_start: Number of random start points, default is 1.
• num_pert: Number of perturbation, default is 100.
• min_theta_range: The lower bound of the uniform distribution for each initial value for theta generated from.
• max_theta_range: The upper bound of the uniform distribution for each initial value for theta generated from.
• maxit: Maximum number of iterations for each optimization, default is 100.
• thres: Threshold for convergence criterion.

Returns

A list

• BIC_theta: Estimated causal effect from MVMR-cML-BIC
• BIC_invalid: Invalid IVs selected by MVMR-cML-BIC
• BIC_DP_theta: Estimated causal effect from MVMR-cML-DP
• BIC_DP_se: Estimate standard error for BIC_DP_theta
• eff_DP_B: Data perturbation with successful convergence
• DP_ninvalid: A vector of the number of selected invalid IVs by MVMRcML-BIC in each data perturbation.