MVmr_cML function

MVMRcML method with Data Perturbation

This is the internal MVMRcML-BIC function of mr_mvcML.

MVmr_cML(
  b_exp,
  b_out,
  se_bx,
  Sig_inv_l,
  n,
  K_vec = as.numeric(c()),
  random_start = 1L,
  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.
• 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
• l_vec: A vector of negative log-likelihood corresponding to each K.
• K_vec: A vector of candidate K's
• theta_vec: A matrix of causal parameter estimates, each column corresponds to a candidate K.
• Conv_vec: A vector of successful convergence indicators corresponding to each K.
• Converge: Indicator of successful convergence, 0 means success, 1 means failure.
• BIC_vec: Data perturbation with successful convergence
• Khat: The length of BIC_invalid.