TSHT.sumstats: TSHT using summary statistics

In MinhaoYaooo/MR.TSHT: Two Sample Mendelian Randomization using Two-stage Hard Thresholding with Voting

TSHT using summary statistics

Description

Conduct two-stage hard thresholding using summary statistics

Usage

TSHT.sumstats(
  ITT_D,
  ITT_Y,
  SE_D,
  SE_Y,
  n1,
  n2,
  tuning = 2.01,
  max_clique = TRUE,
  alpha = 0.05
)

Arguments

ITT_D	a numeric vector of GWAS summary statistics of the treatment
ITT_Y	a numeric vector of GWAS summary statistics of the outcome
SE_D	a numeric vector of standard errors of ITT_D
SE_Y	a numeric vector of standard errors of ITT_Y
n1	the sample size of GWAS summary statistics of the treatment
n2	the sample size of GWAS summary statistics of the outcome
tuning	a numeric scalar value tuning parameter for TSHT, with default 1
max_clique	an option to replace the majority and plurality voting procedures with finding maximal clique in the IV voting matrix, with default FALSE
alpha	a numeric scalar value between 0 and 1 indicating the significance level for the confidence interval, with default 0.05

Value

VHat	a numeric vector denoting the set of valid and relevant IVs
betaHat	a numeric scalar denoting the estimate of treatment effect.
seHat	a numeric scalar denoting the estimated standard error of betaHat.
ci	a two dimensional numeric vector denoting the 1-alpha confidence intervals for betaHat with lower and upper endpoints.

MinhaoYaooo/MR.TSHT documentation built on May 22, 2022, 7:19 a.m.