mr.divw: Main function for dIVW

In tye27/mr.divw: debiased inverse-variance weighted estimator for univariable and multivariable Mendelian randomization

Main function for dIVW

Description

Main function for dIVW

Usage

mr.divw(
  beta.exposure,
  beta.outcome,
  se.exposure,
  se.outcome,
  alpha = 0.05,
  pval.selection = NULL,
  lambda = 0,
  over.dispersion = FALSE,
  diagnostics = FALSE,
  overlap = FALSE,
  gen_cor = 0
)

Arguments

beta.exposure	A vector of SNP effects on the exposure vairable, usually obtained from a GWAS
beta.outcome	A vector of SNP effects on the outcome vairable, usually obtained from a GWAS
se.exposure	A vecor of standard errors of beta.exposure
se.outcome	A vector of standard errors of beta.outcome
alpha	Confidence interval has level 1-alpha
pval.selection	A vector of p-values calculated based on the selection dataset that is used for IV selection. It is not required when lambda=0
lambda	The specified z-score threhold. Default is 0 (without thresholding)
over.dispersion	Should the model consider balanced horizontal pleiotropy. Default is FALSE
diagnostics	Should the function returns the q-q plot for assumption diagnosis. Default is FALSE
overlap	Should the model consider overlapping exposure and outcome datasets. Default is FALSE
gen_cor	If overlap = TRUE, provide an estimate of the correlation between the effect of the genetic variants on the exposure and the outcome. Default value is 0, meaning that the exposure and outcome datasets are non-overlapping.

Value

A list

beta.hat

Estimated causal effect

beta.se

Standard error of beta.hat

condition

A measure that needs to be large for reliable asymptotic approximation based on the dIVW estimator. It is recommended to be greater than 20

tau.square

Overdispersion parameter if over.dispersion=TRUE

n.IV

Number of IVs used in the dIVW estimator

IV

IVs that are used in the dIVW estimator

References

Ting Ye, Jun Shao, Hyunseung Kang (2020). Debiased Inverse-Variance Weighted Estimator in Two-Sample Summary-Data Mendelian Randomization.https://arxiv.org/abs/1911.09802.

Examples

data(bmi.cad)
attach(bmi.cad)
mr.divw(beta.exposure, beta.outcome, se.exposure, se.outcome, diagnostics=TRUE)
detach(bmi.cad)

tye27/mr.divw documentation built on Oct. 18, 2024, 12:06 a.m.