cML_estimate_random {MendelianRandomization}

Estimate with Regular Likelihood Using Multiple Random Start Points

Description

Internal function of mr_cML. Get estimated theta, se of estimated theta and negative log-likelihood, using multiple random starting points.

Usage

cML_estimate_random(
  b_exp,
  b_out,
  se_exp,
  se_out,
  K,
  random_start = 0,
  maxit = 100
)

Arguments

b_exp

Vector of estimated effects for exposure.

b_out

Vector or estimated effects for outcome.

se_exp

Vector of standard errors for exposure.

se_out

Vector of standard errors for outcome.

K

Constraint parameter, number of invalid IVs.

random_start

Number of random starting points, default is 0.

maxit

Maximum number of iteration.

Value

A list contains: theta is the estimate causal effect, se is standard error of estimated theta, l is negative log-likelihood, r_est is estimated r vector.

Examples

cML_estimate_random(b_exp = ldlc,b_out = chdlodds,se_exp = ldlcse,
se_out = chdloddsse, K = 5)